Multicast collaborative erasure encoding and distributed parity protection

ABSTRACT

The present disclosure provides methods and systems for multicast collaborative erasure encoding and methods and systems for distributed parity protection. One embodiment relates to a method of multicast collaborative erasure encoding of a chunk stored in a distributed object storage cluster. A roll-call request is multicast to every storage server in a negotiating group for the chunk. Roll-call inventory responses are generated and multicast by every storage server in the negotiating group. The roll-call inventory responses are collected by every storage server in the negotiating group from other storage servers in the negotiating group to form a set of roll-call inventory responses. A logical evaluation of the set of roll-call inventory responses may then be performed by every storage server in the negotiating group. Other embodiments, aspects and features are also disclosed.

CROSS-REFERENCE TO RELATED APPLICATION(S)

The present application claims the benefit of U.S. Provisional PatentApplication No. 62/040,962, filed Aug. 22, 2014, the disclosure of whichis hereby incorporated by reference in its entirety. The presentapplication also claims the benefit of U.S. Provisional PatentApplication No. 62/098,727, filed Dec. 31, 2014, the disclosure of whichis hereby incorporated by reference in its entirety.

BACKGROUND

1. Technical Field

The present disclosure relates generally to data storage systems anddata communication systems.

2. Description of the Background Art

With the increasing amount of data being created, there is increasingdemand for data storage solutions. Storing data using a cloud storageservice is a solution that is growing in popularity. A cloud storageservice may be publicly-available or private to a particular enterpriseor organization. Popular public cloud storage services include AmazonS3™, the Google File System, and the OpenStack Object Storage (Swift)System™.

Cloud storage systems may provide “get” and “put” access to objects,where an object includes a payload of data being stored. The payload ofan object may be stored in parts referred to as “chunks”. Using chunksenables the parallel transfer of the payload and allows the payload of asingle large object to be spread over multiple storage servers.

SUMMARY

The present disclosure provides methods and systems for multicastcollaborative erasure encoding and methods and systems for distributedparity protection.

One embodiment relates to a method of multicast collaborative erasureencoding of a chunk stored in a distributed object storage cluster. Aroll-call request is multicast to every storage server in a negotiatinggroup for the chunk. Roll-call inventory responses are generated andmulticast by every storage server in the negotiating group. Theroll-call inventory responses are collected by every storage server inthe negotiating group from other storage servers in the negotiatinggroup to form a set of roll-call inventory responses. A logicalevaluation of the set of roll-call inventory responses may then beperformed by every storage server in the negotiating group.

Another embodiment relates to a distributed object storage system thatstores objects in chunks. The system includes a plurality of storageservers communicatively interconnected by a network, and negotiatinggroups for the chunks. A negotiating group for a chunk comprises a groupof the storage servers that are assigned to store and provide access tothe chunk. A storage server in the negotiating group for the chunkincludes executable code that performs steps including: multicasting aroll-call request to other storage servers in the negotiating group forthe chunk; collecting roll-call inventory responses received from theother storage servers in the negotiating group for the chunk to form aset of roll-call inventory responses; and performing a logicalevaluation of the set of roll-call inventory responses.

Another embodiment relates to a storage server in a distributed objectstorage system that stores objects in chunks. The storage serverincludes: a processor for executing executable code; memory for storingand accessing executable code and data; and a network connection tocommunicatively interconnect the storage server with other storageservers in the distributed object storage system. The executable codeperforms steps that include: multicasting a roll-call request to a groupof storage servers that are responsible for storing and providing accessto a chunk; collecting roll-call inventory responses received from thestorage servers in the group to form a set of roll-call inventoryresponses; and performing a logical evaluation of the set of roll-callinventory responses. The logical evaluation may result in a subset ofactions to be performed by the storage server.

In another embodiment, the storage server includes executable code,where the executable code performs steps that include: receiving aroll-call request for the chunk; multicasting a roll-call inventoryresponse to the negotiating group in response to the roll-call request;collecting roll-call inventory responses received from other storageservers in the negotiating group to form a set of roll-call inventoryresponses; and performing a logical evaluation of the set of roll-callinventory responses. The logical evaluation may result in a subset ofactions to be performed by the storage server.

Another embodiment relates to a method of distributed parity protectionof a chunk stored in an object storage cluster. The chunk is stored in aplurality of erasure-encoded slices at different storage servers in theobject storage cluster, wherein the plurality of erasure-encoded slicesinclude a plurality of data stripes and at least one parity stripe. Adetermination is made that a data stripe of the plurality of datastripes is lost, and a further determination is made as to the survivingerasure-encoded slices of the plurality of erasure-encoded slices. Thesurviving erasure-encoded slices are grouped into a first set of pairsby having a first storage server holding a first slice of each pair sendthe first slice to a second storage server holding a second slice of thepair. The second storage server applies an operation on the first andsecond slices to generate a resultant slice. The resultant slices may befurther grouped and operated upon until a single slice is generated, thesingle slice being the data stripe that was lost.

Another embodiment relates to an object storage system with distributedparity protection. The system includes a network and a plurality ofstorage servers communicatively interconnected by the network. Theplurality of storage servers include executable code that performs thefollowing steps: storing a chunk in a plurality of erasure-encodedslices at different storage servers, wherein the plurality oferasure-encoded slices include a plurality of data stripes and at leastone parity stripe; determining that a data stripe of the plurality ofdata stripes is lost; determining surviving erasure-encoded slices ofthe plurality of erasure-encoded slices; grouping the survivingerasure-encoded slices into a first set of pairs by sending a firsterasure-encoded slice of each pair from a first storage server to asecond storage server that holds a second erasure-encoded slice of eachpair; and operating on first and second slices of each pair in the firstset of pairs to generate a set of resultant slices at the second storageserver. The resultant slices may be further grouped and operated uponuntil a single slice is generated, the single slice being the datastripe that was lost.

Other embodiments, aspects, and features are also disclosed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a non-blocking switch.

FIG. 2 depicts where the replicast transport layer may fit into theconventional OSI/ISO Seven Layer Model in accordance with an embodimentof the invention.

FIG. 3 is a simplified depiction of chunk transmission in an exemplarydistributed storage system in accordance with an embodiment of theinvention.

FIG. 4 depicts congestion on inbound links of a distributed storagesystem with serial transmission of chunk copies.

FIG. 5 depicts a distributed chunk put operation using relayed unicasttransmission in a distributed storage system.

FIGS. 6-8 depict steps of a client-consensus-based procedure forproposing a chunk put to a distributed storage system in accordance withan embodiment of the invention.

FIGS. 9-11 depict steps of a cluster-consensus-based procedure forproposing a chunk put to a distributed storage system in accordance withan embodiment of the invention.

FIGS. 12 and 13 depict steps of a client-consensus-based procedure forproposing a chunk put to a distributed storage system withde-duplication in accordance with an embodiment of the invention.

FIGS. 14 and 15 depict steps of a cluster-consensus-based procedure forproposing a chunk put to a distributed storage system withde-duplication in accordance with an embodiment of the invention.

FIGS. 16 and 17 depict steps of a client-consensus-based procedure forrequesting a chunk get from a distributed storage system in accordancewith an embodiment of the invention.

FIGS. 18 and 19 depict steps of a cluster-consensus-based procedure forrequesting a chunk get from a distributed storage system in accordancewith an embodiment of the invention.

FIGS. 20 and 21 depict steps of a cluster-consensus-based procedure forrequesting a chunk get from a distributed storage system where anadditional target is requested in accordance with an embodiment of theinvention.

FIGS. 22 and 23 depict a possible encoding of a generic “Replicast”message over L2 frames.

FIG. 24 depicts exemplary encoding structures for chunk put proposalmessages in accordance with an embodiment of the invention.

FIG. 25 depicts exemplary encoding structures for chunk accept messagesin accordance with an embodiment of the invention.

FIG. 26 depicts exemplary encoding structures for rendezvous transfermessages in accordance with an embodiment of the invention.

FIG. 27 depicts exemplary encoding structures for payloadacknowledgement messages in accordance with an embodiment of theinvention.

FIG. 28 depicts exemplary encoding structures for get request messagesin accordance with an embodiment of the invention.

FIG. 29 depicts exemplary encoding structures for get response messagesin accordance with an embodiment of the invention.

FIG. 30 depicts exemplary encoding structures for an error get responsemessage in accordance with an embodiment of the invention.

FIG. 31 depicts a simplified example of a computer apparatus which maybe configured as a client or a server in the system in accordance withan embodiment of the invention.

FIG. 32 depicts a process for weighting servers in an object storagesystem in accordance with an embodiment of the invention.

FIG. 33 depicts a sample assignment of server IDs to rows of a hashtable for an object storage system in accordance with an embodiment ofthe invention.

FIG. 34 depicts processing of a chunk hash ID to determine a set ofserver IDs in an object storage system in accordance with an embodimentof the invention.

FIG. 35 is a flow chart of a method of multicast collaborative erasureencoding of a chunk that is stored in an object storage system inaccordance with an embodiment of the invention.

FIG. 36 is a state diagram showing macro-states for chunk encoding inaccordance with an embodiment of the invention.

FIG. 37 depicts a method of conventional recovery of a lost stripe froma parity stripe.

FIG. 38 depicts a method of distributed recovery of a lost stripe from aparity stripe in accordance with an embodiment of the invention.

DETAILED DESCRIPTION

I. Scalable Transport for Multicast Replication

As described herein, multicast communications may provide great value instorage networking. There are several instances where the desireddistribution of information is from one sender to multiple receivers.These include:

-   1) Replication of storage content. Creating more than one replica is    generally desired to protect against the loss of individual storage    servers.-   2) Finding the most suitable set of storage servers to accept new    content. Storage servers have dynamically varying capacities and    work queue depths. Finding the servers that could store the content    most quickly allows transactions to complete in the shortest    possible time. If point-to-point protocols performed this survey,    the polling process could easily take more time than the potential    savings in time.-   3) Finding the best storage server to process a specific get request    has similar issues as finding the most suitable set of storage    servers to accept new content.-   4) Network replication to additional servers in order to create    extra replicas for caching content, distributing content to archival    storage and to remote networks comes with only minimal network    traffic increase and no increase in server operations for reading    the extra copies for these separate purposes.-   5) Enabling parallel updating of distributed content (e.g. a    Distributed Hash Allocation Table) on all cluster members.

While the value of these potential multicast communications is clear,the conventional wisdom has been that multicast cannot be reliableenough for storage, and therefore the overhead of point-to-pointprotocols must be tolerated in order to provide reliability. Use ofmulticast in storage clusters has been conventionally limited to the“keep-alive” protocols, which track the set of storage servers currentlyconnected. Conventionally multicast messaging is not used for thestorage content itself.

The present disclosure provides an effectively reliable transport layerfor multicast communications. The methods disclosed herein are optimizedfor storage networking within a local area network with short andreasonably uniform round-trip times, but they may be layered on top ofany transport services that provides an unreliable datagram service andmulticast addressing.

Congestion Control in Point-to-Point Network Replication

Replicating storage over a shared network typically involves largetransfers initiated independently by multiple sources. In such cases,some form of congestion control is required to avoid over-subscribingthe buffering capacity of the storage network. Designing a core networkto be non-blocking is feasible and desirable; however, it is currentlyimplausible to design the target nodes with enough capacity to receiveconcurrent transfers from every source that might want to transmit.Moreover, even with a non-blocking core, some form of congestion controlis required to allocate the bandwidth on the last link to the targetservers.

In a simple solution, each content source replicates content to eachdistinct storage server using Unicast point-to-point reliableconnections (most frequently TCP/IP). However, this solution can makethe link from the content source a bottleneck that limits the speed ofsending the new content into the network. According to this solution, ifK is the desired replication count (e.g., three), then the source serversends the content K times (each time over a point-to-point connection).The OpenStack Object Service (“Swift”) has this design characteristic.

Another Object Storage system, the Hadoop Distributed File System(HDFS), partially addresses this problem by serializing replication ofnew content. The content source puts to a first storage server, whichthen replicates that chunk to a second storage server, which thenreplicates it to a third storage server. If the server performsreplication on a cut-through basis, the impact on an isolated puttransaction would appear to be minimal (two times the cut-throughlatency, which might be as small as a single Ethernet frame for eachhop).

However, such an analysis ignores the problem that the servers that arereceiving chunks or objects must also retrieve and deliver content ondemand. Most object storage systems operate in a write-once read-many(WORM) fashion. When a storage server takes responsibility forreplicating new content the server has the limitation that thereplication bandwidth is in contention with retrieval bandwidth. Theonly way to avoid congestion drops is to delay either the replicationtraffic or the retrieval traffic. The latency for puts and/or reads(gets) will suffer because of this contention.

To optimize replication of content in distributed storage systems, thepresently-disclosed solution multicasts the content so as to optimizeboth the load on the servers and the shaping of the network traffic.While it is desirable to multicast replication traffic, doing so shouldnot be allowed to cause network congestion and resulting droppedpackets. Hence, as further disclosed herein, packet drops may be dealtwith by retransmission using unicast replication on a point-to-pointbasis.

Reasons why Multicast was not Used in the Past

This section describes some reasons why applicants believe thatmulticast has not been used in the past for replication of storedcontent.

It would be optimum for storage networking to put the content to thenetwork once and have that content reliably arrive at each of Ndestinations. One challenge to achieving this optimum result is thateach chunk is typically encoded as multiple L2 (layer 2) frames. L2networking protocols, such as Ethernet or InfiniBand™, have individualframes that are small compared to the size of the typical chunk saved ina storage system. For example in a single user Ubuntu workstation withover 584,843 files, the average file size is 240,736 bytes, (totaling˜140 GB) although the median file size is only 3,472 bytes and thelargest file is 2.9 GB. Hence, a typical put (or get) will need todeliver very many L2 frames without any portion of the message beingdropped.

Modern wired networks have exceedingly low error rates on rawtransmission. Therefore, when a message is comprised of hundreds of L2frames the most common cause of non-delivery of a message iscongestion-induced drops. Message drops caused by a transmission erroron even one of hundreds of frames are exceptionally rare.

With unicast delivery, the transport protocol acknowledges each packetwithin the overall message (typically only sending the acknowledgementfor every other packet). However, typical point-to-point transportprotocols negotiate a packet or byte sequence number during connectionestablishment. It is not feasible to simply multicast a TCP packet tomultiple receivers and simply collect the acknowledgements from eachtarget because each target will have selected a different randomstarting sequence for itself. With TCP, for example, network elementswould have to modify the TCP sequence number for each target.

Generally, multicast delivery has been limited to unreliable delivery orhas relied on negative acknowledgements to allow limited retransmissionrequests.

The challenges of using multicast distribution for reliable delivery ofbulk payload has limited deployment of multicast addressing withinstorage clusters to control plane functions such as node discovery,health checking and negotiating which server would be assigned to storeeach object. However, conventional unicast protocols have been used toreliably transfer bulk payload. As desirable as sending once andreceiving multiple times would be, the conventional wisdom has been thatthis cannot be achieved with reliable delivery.

Splitting the traffic submitted once within the network to multipledestinations is challenging with TCP-like protocols. Either the splittermust act as a full application layer gateway, complete with providingpersistent storage for all payload it has acknowledged until the gatewayitself has been acknowledged by each target, or it must spoof flowcontrol responses from the splice point such that no packet isoriginated until there is a window for delivery to each of the targets,and it acknowledges no packet until it has been acknowledged by alltargets. Such a gateway would also have to track which targets hadacknowledged a given packet and only forward retransmitted packets tothose targets that had not already acknowledged it. Re-transmitting anacknowledged packet will cause the destination to conclude that itsacknowledgement had not been received, from which it would infer thatthe network must be congested.

Advantageously, the use of multicast addressing is far simpler. At thenetwork layer, multicast protocols are unreliable. Hence, no tracking ofper-packet reception is required.

Utilizing multicast addressing allows new payloads to enter theswitching fabric once, and then deliver them to N destinations. Theprotocol may then advantageously track the delivery of the entiremessage rather the tracking the delivery of individual packets. Whencongestion control properly minimizes the risk of congestion drops, theresulting delivery becomes reliable enough that per packetacknowledgements are no longer required. Hence, in accordance with anembodiment of the present invention, reliable delivery may be achievedusing a simpler and more efficient transport protocol. In addition, theutilization of the switching fabrics buffers may be radically reduced,achieving more efficient distribution and more effective utilization ofthe network.

Conventional point-to-point transport protocols rely on per-packet errordetection. However, with modern wired networks, applicants believe thatprotecting data integrity for the entire message is more effective. Thisis because layer 2 error checking ensures that very few packets haveundetected errors, and retransmission of the entire message isacceptable when it is seldom required.

As described herein, a congestion control protocol may be designed forenvironments where there is no congestion on the core links and packetsdropped due to transmission errors are extremely rare by avoidingcongestion on the edge links to Ethernet end stations. In particular, acongestion control protocol that prevented concurrent bulk transfers toa given egress link would make it safe to transmit the entire chunk witha single ACK/NAK. Retransmission of the entire chunk would be requiredafter an unsuccessful delivery attempt, but this is a cost easilycarried if congestion drops have been avoided and dropped frames areextremely rare. The benefits of a simplified protocol, and lesserbandwidth required for acknowledgements themselves, would compensate forthe extremely rare retransmission. Combined with the benefits ofmulticasting, such a congestion control protocol that enablescoordination of bulk data transfers in a way that avoids edge linkcongestion-induced packet drops should generally improve overall networkutilization.

Note that the ability to avoid congestion by scheduling delivery ofmessages at a higher layer is dependent on networking layer 2 providingsome basic traffic shaping and congestion avoidance on its own.

L2 Traffic Shaping Capabilities

The presently-disclosed solution utilizes edge-based congestion controlfor multicast messages. To understand how edge-based congestion controlcan avoid congestion-based drops of the layer 2 (L2) frames, it isuseful to first review the traffic shaping capabilities of advancedEthernet switches. In relation to such traffic shaping capabilities, thefollowing discusses a non-blocking switch, a non-blocking core, multipletraffic classes, and protected traffic classes.

1) Non-Blocking Switch

A switch can be considered to be non-blocking if it is capable ofrunning every one of its links at full capacity without dropping frames,as long as the traffic was distributed such that it did not exceed thecapacity on any one of its links. For example, a non-blocking eight-portswitch could relay traffic between four pairs of end stations at fullwire speed.

More usefully, each of the eight ports could be sending 1/7th of thewire speed to each of the other ports. A non-blocking switch hassufficient internal buffering so it can queue the output frames to anyone of its ports. The other ports can “share” this output without havingto synchronize their transmissions. If they each have a sustained rateof 1/7th of the wire capacity then the output queue for the target portmay grow temporarily, but it will not grow indefinitely. There arewell-known algorithms to determine the maximum buffering capacityrequired.

A non-blocking switch may offer service level agreements (SLAs) to itsend stations that are capable of providing a sustained level ofthroughput to each of its ports, as long as no egress port isover-subscribed on a sustained basis. Referring now to FIG. 1, theillustrated switch provides a non-blocking switch fabric, such that aflow from X to Y cannot be adversely impacted by any flow from I to J.

2) Non-Blocking Core

A non-blocking core is a collection of non-blocking switches that havesufficient bandwidth between the switches such that they can effectivelyact as though they were simply a large aggregate switch.

3) Multiple Traffic Classes

Switches typically offer multiple traffic classes. Frames are queuedbased upon the egress port, Ethernet class of service, and other factorssuch as VLAN (virtual local area network) tags.

Usually these queues do not represent buffers permanently assigned toseparate queues, but rather just a method for accounting for bufferusage. When a queue is assigned N buffers it does not mean that Nbuffers are identified in advance. Rather it means that the number ofbuffers the queue is using is tracked, and if it exceeds N the excessbuffers are subject to being dropped.

Advanced switches are capable of monitoring the depth of queues formultiple traffic classes and potentially taking action based on queuedepth (marking excessive traffic, generating congestion notifications,or simply dropped non-compliant frames). The traffic class configurationis typically a steady configuration item for any switch. Well knownalgorithms allow the switch to enforce that a given traffic class willbe able to sustain X Gb/sec without requiring the switch to track thestate of each flow through the switch.

4) Protected Traffic Classes

A Protected Traffic Class is a traffic class that is reserved for aspecific use. The network forwarding elements are configured to knowwhich ports are members of the protected traffic class. L2 frames thatare marked as part of a protected traffic class, but arrive fromunauthorized ports, are simply dropped. Typically switches will alsoblock, or at least limit, relaying frames in a protected traffic classto non-member ports.

FCoE (Fibre Channel Over Ethernet) is one example of a protocol which isdependent on a protected traffic class. The protocol is not robust ifnon-compliant frames can be accepted from unauthorized ports.

Replicast Transport Layer

The present section details a “Replicast” transport layer in accordancewith an embodiment of the present invention. In one implementation, theReplicast transport layer operates in conjunction with a distributedstorage layer for a distributed object storage system. FIG. 2illustrates the conventional model and where Replicast transport layerand distributed storage layers may be inserted into that model as “Layer4.5” between the conventional transport layer 4 and the conventionalsession layer 5.

While the present section details a Replicast transport service that isintended for usage by a distributed object storage system, the specificmulticast messaging capabilities provided are not constrained to supportonly distributed object storage. Other applications can benefit from thepresently-disclosed Replicast transport services. For example, a methodfor replicating file system images between file servers could also usethe Replicast transport services disclosed herein. One example of thiswould be ZFS file servers replicating the output of the “zfs send”utility.

The following Table 1 itemizes the assignment of responsibilitiesbetween the Replicast transport layer disclosed in the present sectionand an example distributed storage layer that may be supported by theReplicast transport layer:

TABLE 1 Division of responsibilities between Replicast transport anddistributed storage layers Responsibility Layer Comment Detection ofTransport A hash signature is calculated for all trans- transmissionferred content. error. Detection Transport Messages with lost packetswill fail the of lost L3 signature test for the complete message.packets Packets are sequenced within a message, allowing forcheckerboard testing for reception of the complete message. DetectionStorage The transport layer will only detect messages of lost L5 thatare partially lost, not any that are messages completely lost. Thestorage layer must detect missing messages and responses. DeterminationStorage The transport layer can detect whether of success specificrecipients successfully received a message without corruption, but itcannot determine whether the overall message was delivered to asufficient set of recipients. Retry of L5 Storage The transport layerdetects failure of indi- message vidual deliveries. The storage layermust determines when and if a given message will be retried. Pacing ofStorage The transport layer indicates how often the Unsolicited storagelayer may transmit unsolicited Messages messages, but it does not pacethose deliveries itself. Rather it relies on the storage layer to choosewhich messages to submit to comply with the rate published. CongestionTransport The transport layer works with L2 conges- Avoidance tionavoidance techniques (such as IEEE 802.1 DCB—Data Center Bridging) pro-tocols to provide delivery of unreliable datagrams without droppingpackets due to congestion. Note that IEEE 802.1 DCB is only onemechanism for achieving drop- resistant L2 delivery that is protectedfrom other traffic classes. Traffic Storage The primary congestionavoidance technique Selection used is to perform most bulk contenttransfer (i.e. Shaping with reserved bandwidth. The transport layerStorage enforces reservations, but the storage layer Traffic or chooseswhich reservations to grant by Selection of determining when eachstorage server would content when be capable of doing a specifiedrendezvous competing for transfer. The present invention does notlimited band- specify what algorithm any storage server in width) thecluster will use when proposing rendez- vous transfer times based uponits current workload. There are many well = -known algorithms for makingsuch estimates, deter- mination of which algorithms are most costeffective for which storage resources is left to each specificembodiment. Distributed Storage The storage layer determines when aDeduplication proposed transfer is not needed because the content isalready stored locally. The trans- port layer merely relays thisinformation. Management Enhanced The L2 layer is responsible forprotecting of bandwidth L2 (such the traffic class from other traffic.Presum- between as DCB) ably, it also protects the other traffic fromTraffic the storage traffic class. Classes Management Transport Thetransport layer is responsible for of bandwidth allocating the bandwidthprovided by L2 within the layer to specific messages and transfers.storage traffic class Transmit at Transport Datagrams are transmittedonce and are most once typically delivered to all members of the targetmulticast group. Datagrams cannot be delivered more than once becauseeach L2 message is uniquely identified by source and sequence number.Further, each datagram is identified as a specific fragment of an L5message. Packets that are duplicate receptions are discarded. DatagramTransport Unreliable datagrams are labeled as to sequencing theirsequencing within an L5 message. Multicast unreliable Such asUDP/IP/Ethernet or UD/InfiniBand. addressing datagram service

Edge Managed Flow Control

The present disclosure combines the lack of central bottlenecks with theability to factor dynamic storage-server specific metrics, such asavailable storage capacity, work queue depth and network congestion onthe storage server's ingress ports.

An overly simplified analysis would seek to have every storage serverevaluate its own suitability for storing a specific chunk, and thenhaving the source select the number (n) of storage servers with thehighest score. However, this would not scale as the total number (N) ofstorage servers in a cluster increased. As disclosed herein, a scalablemethodology, instead, controls the total number of requests made to eachstorage server. Ideally, as the cluster workload grows, the number ofrequests per server can be held nearly constant by adding servers andnetwork bandwidth. This will allow the entire cluster to scale in anearly linear fashion.

The present disclosure accomplishes holding nearly constant the numberof requests per server by selecting a subset of the storage servers toprocess requests related to any specific chunk. The present disclosurerefers to this subset as the “Negotiating Group”. The Negotiating Groupwill select specific storage servers from the group to store thespecific chunk. Generally, the number of members in a Negotiating Groupshould be kept stable even as the number of storage servers grows. Thecomplexity of the negotiation process is determined by the number ofstorage servers in the Negotiating Group, not by the size of the entirecluster.

Referring now to Table 2, an exemplary size (n) of the Negotiating Groupis that it should scale to on the order of K multiplied by Log₁₀(N)[i.e. should scale to O(K*Log₁₀(N)], where K is a function of thestorage replication count, and where N is the total number of clustermembers. K may typically vary from one to five. Hence, as shown in Table2, depending on the value of K, for 100 servers in the cluster, thereshould be two to ten members of the Negotiating Group, and for 10,000servers in the cluster, there should be four to twenty members of theNegotiating Group.

TABLE 2 Number of Designated Servers in a Negotiating Group for aCluster Replication Cluster Members K = 1 K = 2 K = 3 K = 4 K = 5 100 24 6 8 10 1,000 3 6 9 12 15 10,000 4 8 12 16 20

In an exemplary implementation, the server performing the “put”operation for a chunk will select a set of servers from the NegotiatingGroup. The selection method is not dependent on a central process orbottleneck and is capable of adapting to storage server backlogs andcapacity.

In an exemplary selection method, all members of the Negotiating groupreceive a proposal to store the new chunk (i.e. a Put Proposal) viamulticast-addressed UDP datagrams, without adding extra transmissionburden on the source server. The source chooses the Negotiating Group bymapping the appropriate Chunk Hash ID to a Distributed Hash AllocationTable so as to specify the membership of the Negotiating Group andidentify its members. A Chunk Hash ID may be a cryptographic hash ofeither a chunk's payload (for chunks that hold only payload) or of theidentity of the object (for chunks holding metadata). In an exemplaryembodiment, this mapping is accomplished by indexing one row from ashared Distributed Hash Allocation Table. In an exemplaryimplementation, each chunk may have a unique identifier that effectivelyincorporates distributed deduplication into the distribution algorithm,making the implementation highly tailored for document storageapplications. There are existing techniques that allow distributeddeduplication to co-exist with the provision of cryptographic protectionfor document content.

It should be understood that the “Distributed Hash Allocation Table”need not be an actual table fully implemented on every node of thenetwork. It is sufficient that each row of the table maps to a multicastaddress, and that the network's multicast forwarding be configured sothat a multicast message will be delivered to the members of the row.Existing protocols for controlling multicast forwarding can therefore beused to implement the “Distributed Hash Allocation Table” even if theydo not consider the tables they manipulate to be anything more thanmulticast forwarding tables.

Referring back to the exemplary selection method, each recipient of thePut Proposal calculates when and if it could accept the chunk, orwhether it already has the indicated chunk. The recipient returns a PutAccept message with the appropriate indication to not only the source,but to all other members of the Negotiation Group. Limitations on therecipient's available storage that make this specific storage serverless desirable as a target are reflected by making this storage serverless prompt in acknowledging the proposal or in scheduling the receiptof the chunk. Additional considerations are possible to indicate thatperhaps the recipient has a heavy workload and, if there are otherrecipients with less workload, that their responses may also be moreprompt.

While the present disclosure is not necessarily limited to storageservers, in most embodiments, the storage servers will utilize theentire bandwidth available to a single reservation at a time. Inaccordance with the present disclosure, there is no benefit todelivering part of a chunk. Therefore, it will generally be desirable tofinish each request as early as possible, even if it means delaying thestart of the transfer of a later request. It is the aggregate completiontimes for the transfers that matters. By contrast, conventional filesystems will generally seek to make forward progress for all transfersin parallel.

Upon the collection of the responses from the Negotiating Group withinthe timeout window, the Chunk Source decides whether to deliver theChunk payload in order to increase the number of replicas. If so, itcreates the Rendezvous Group, which is a subset of the NegotiatingGroup. In the exemplary implementation, other members of the negotiatinggroup may also see this response and update their list of designatedservers that hold a copy of the Chunk.

The present disclosure also provides for efficient replication ofcontent to the Rendezvous Group by relying on the rendezvous negotiationto eliminate the need for sustained congestion control for a multicastChunk Put or conventional point-to-point reliable transport protocols.

Exemplary Storage Cluster

FIG. 3 is a simplified depiction of chunk transmission in an exemplarystorage cluster in accordance with an embodiment of the invention. Asshown in FIG. 3, there is a cluster 100 of servers and clients. Theservers 102 through 112 are connected to Ethernet switches 115 and 116.While several servers and two switches are depicted, an implementedstorage cluster may have a multitude of servers and a larger number ofswitches. The switches, in turn, may be connected to each other by oneor more Ethernet trunk 127. In an exemplary implementation, the switchesmay be non-blocking switches, and the switches together with theinterconnecting trunks may form a non-blocking core.

In this depiction, Chunk A 117 is sent from user client 101 to networkswitch 115 and is multicast replicated to Server 103 as Chunk A 118,Server 106 as Chunk A 119, Server 112 as Chunk A 120. Chunk B 121 issent from user client 114 to switch 115 and is replicated to Server 102as Chunk B 122, through trunk 127 to switch 116 and then to Server 107as Chunk B 123 and to Server 110 as Chunk B 124. At the same time Server102 is returning Chunk C 125 via Switch 115 to client user 113 as ChunkC 126.

Serial Transmission of Chunk Copies

FIG. 4 depicts congestion on inbound links of a distributed storagesystem with serial transmission of chunk copies. Such serialtransmission of chunk copies is utilized, for example, in the OpenStackObject Service. The servers, clients, switches and trunks of FIG. 4 maybe arranged as described above in relation to FIG. 3.

As depicted in FIG. 4, we see that Chunks A1 117, A2 118 and A3 119 (allcopies of Chunk A) are transmitted sequentially through the connectionbetween the user client machine 101 and the Ethernet switch 115. Fromthat point, Chunk A1 121 is sent to the target server 106, Chunk A2 120is sent to a different server 103 and Chunk A3 122 to a third server112. Similarly the chunks B1 123, B2 124 and B3 125 (all copies of ChunkB) are transmitted from user client 114 to Ethernet switch 115 insequential fashion, even though they are all copies of the same chunk B.From that point, the B1 Chunk 126, B2 Chunk 127 and B3 Chunk 128 aresent to separate servers. In addition, the C1 Chunk illustrates that, inaddition to the PUT activities for Chunks A and B, users are alsoperforming GETs of data. In particular, the C1 Chunk 129 is sent fromthe server 102 to the switch 115, and then the C1 Chunk 130 is sent tothe user client 113.

Relayed Unicast Transmission

FIG. 5 depicts a distributed chunk put operation using relayed unicasttransmission in a distributed storage system. Such a relayed unicast putis utilized, for example, in the HDFS. The servers, clients, switchesand trunks of FIG. 5 may be arranged as described above in relation toFIG. 3.

In the illustration of FIG. 5, we walk through a sequence of events. Thefirst event is that the user Client 101 transmits the first copy ofChunk A, namely Chunk A1 117, which is received by Server 106 as ChunkA1 118. In preferred implementations, while the Chunk A1 118 is beingreceived, the Server 106 begins a “Cut-through” transmission(illustrated here by the ingress and egress of 118 and 119 overlappingeach other) to start transmitting Chunk A2 119 which is a copy of ChunkA1. Other implementations are possible, including waiting until Chunk A1118 is completely received prior to transmitting Chunk A2 119, but areless optimal. Chunk A2 120 is received by Server 103, copied andretransmitted as Chunk A3 121 (here again illustrated by the ingress andegress of 120 and 121) and finally received by Server 112 as Chunk A3123.

Similarly, the user Client 114 transmits the first copy of Chunk B,namely Chunk B1 124, which is received by Server 107 as Chunk B1 125. Inpreferred implementations, while the Chunk B1 125 is being received, theServer 107 begins a “Cut-through” transmission (illustrated here by theingress and egress of 125 and 126 overlapping each other) to starttransmitting Chunk B2 126 which is a copy of Chunk B1. Chunk B2 127 isreceived by Server 102, copied and retransmitted as Chunk B3 128 (hereagain illustrated by the ingress and egress of 127 and 128) and finallyreceived by Server 110 as Chunk B3 129. In this case, the retransmissionof Chunk B3 128 may be delayed by the transmission of an asynchronous“get” operation which requested Chunk C 130. In this way, otheroperations on the Servers performing “get” operations (to retrieve dataupon request) may slow down the replication of packets by the Servers.

The C Chunk illustrates that, in addition to the PUT activities forChunks A and B, users are also performing GETs of data. In particular,the C Chunk 130 is sent from the server 102 to the switch 115, and thenthe C Chunk 131 is sent to the user client 113.

Overview of Replicast Transport Protocol

The present disclosure provides a method of supporting effectivelyreliable message exchange and rendezvous payload transfers within amulticast group or subsets of the multicast group (possibly combinedwith an external client). An exemplary implementation of the disclosedmethod may be referred to herein as the “Replicast” transport protocol.

The Replicast transport protocol sends unreliable datagrams over aprotected traffic class. Protected traffic classes are a knownnetworking mechanism used in many different IEEE 802.1 protocols. Oneexample particularly relevant for storage networking is FCoE (FibreChannel over Ethernet). The requirements for a protected traffic classmay be summarized as follows.

-   -   L2 frames are admitted to this traffic class only from        explicitly authorized end stations.    -   L2 frames are only delivered to members of the group.    -   As long as this traffic class is in compliance with a bandwidth        budget provisioned for it, its frames will not be dropped due to        congestion caused by L2 frames from other traffic classes.

Effective Reliability

A goal of the Replicast transport layer (when it is used by adistributed storage application) is to enable effectively reliabletransfer of chunks and associated tracking data within a storage clusterand to/from its clients. Distributed storage applications frequentlyneed to make multiple replicas of storage chunks. Enabling aneffectively reliable multicast replication may radically improve theefficiency of network utilization and the efficiency of server resourcesin a cluster.

The Replicast transport layer disclosed herein is optimized for networkswhere actual transmission errors are rare. In such networks, packets aretypically dropped due oversubscription of either forwarding or receivingbuffers.

Distributed storage applications supported by the Replicast transportprotocol preferably may be expected to require more thorough validationof successful transfer of data than is supported by conventionalpoint-to-point transport protocols (such as InfiniBand ReliableConnection, TCP/IP or SCTP/IP). To support more thorough validation ofsuccessful transfers, the Replicast transport protocol disclosed hereinprovides hash signatures for the entire chunk and self-validatingtracking data which may be used to validate successful transfers. Thesemeasures allow incomplete or corrupted transfers to be detected by andreported to the upper layers. For example, a multicast transmission of achunk may be successfully received by 5 out 7 target nodes. The questionof whether that is a “successful” delivery may be properly answered atan upper layer; it is not something the transport layer can or shoulddetermine.

Congestion Avoidance

The present disclosure utilizes an assumption that the lower-layertransports (below the Replicast transport layer) provide at leastminimal congestion avoidance features that can deal with short-livedcongestion without dropping frames. The IEEE 802.1 Data Center Bridging(DCB) protocols are an example implementation of a suitable lower layertransport. Another goal of the Replicast transport layer disclosedherein is to further avoid congestion, particularly congestion over asustained duration. The Replicast Transport layer strives to complementthe existing lower layer solutions (such as DCB) to short-termcongestion with solutions that avoid sustained over-commits ofbandwidth.

Unsolicited vs. Solicited Bandwidth

The present disclosure seeks to effectively eliminate the risk of acongestion drop by tracking its own usage of unsolicited bandwidth,issuing its own reservations for solicited bandwidth, and relying on thelower transport layers to resolve very short span over-subscriptions andprotect the traffic class from traffic from other classes.

Network administration will specify four bandwidth allocations for eachparticipant in the protected traffic class:

-   -   Unsolicited inbound rate: Using known techniques, this        translates to a required amount of buffering to receive        unsolicited packets.    -   Unsolicited outbound rate: A base rate for transmission of        unreliable datagrams that have no reservation. This rate may be        adjusted dynamically by other sources of information. One source        that must be used is the number of failed deliveries on prior        attempts to transmit this datagram. This technique is known as        the Aloha back-off algorithm.    -   Reserved outbound rate: This may limit the aggregate bandwidth        of all rendezvous transmissions from this storage node. This        limit would seldom be reached, so some embodiments may omit this        from their implementation. One deployment where it would be        useful is when the same node was also originating traffic from a        different traffic class.    -   Reserved inbound rate: This node must limit the reservations it        grants so that this rate is never exceeded.

The disclosed congestion avoidance method may be, therefore:

-   1) Provision buffering for reception and in-network forward elements    adequate for both the Unsolicited and Solicited traffic. Unsolicited    traffic is subject to peaks because there is no advance permission    granted before a request is transmitted. Therefore, more buffering    is needed to support a specific bandwidth when using Unsolicited    messaging than would be required for reserved bandwidth.-   2) Limiting transmission rates of unsolicited messages so that the    probability of packet drop is low.-   3) Utilizing Aloha-style random back-offs of retransmissions of    Unsolicited messages used for requests.

Distributing and Retrieving Chunks

The presently-disclosed Replicast transport layer relies on the layerabove it, a distributed storage system in one embodiment, to specify thefollowing:

-   1) A Negotiating Group, which is a multicast group that will conduct    the negotiation to determine the Rendezvous Group, and may determine    the source for a data transfer in a get transaction.-   2) A Rendezvous Group, which is a multicast group that will receive    a data transfer. For a put transaction this group will be a subset    of the Negotiating Group. For a get transaction this group will    include the client or proxy that initiated the get transaction and    may include other members of the Negotiating Group that wish to    receive opportunistic copies of the chunk that has been requested.-   3) A base bandwidth quota for unsolicited traffic that this node may    generate to a specified traffic class. This quota is across support    for all requests. This quota may be dynamically adjusted by many    sources of information as to the congestion state of the network. At    the minimum this set must include the number of recent messages sent    by this node for which there was no timely response. It may include    other sources of network status that are correlated with the    congestion state of the network, including:    -   a) Measured queue depths on forwarding elements for queues that        support this traffic class.    -   b) Receipt of packets for this traffic class which were        explicitly marked to indicate congestion.    -   c) An increase in the one-way delay of packets for this traffic        class through the network.    -   d) Reports of congestion from other nodes participating in this        traffic class.-   4) A bandwidth for this node to receive solicited transfers. The    node will not grant reservations that exceed this quota.

Messages may be addressed to either Negotiating Groups and/or toRendezvous Groups.

A negotiation is conducted within the Negotiation Group using unreliabledatagrams sent with multicast addressing, as described in further detailbelow, to select a subset of those servers to which the bulk messagemust be delivered (or replicated at).

The purpose of the presently-disclosed transport is to deliver “chunks”,which are large collection of bytes used by the upper layer, to theRendezvous Group negotiated in the transaction. Additionally, a set ofopaque “transaction tokens” may be associated with each chunk andupdated in each transfer.

Typical uses of “chunks” by a distributed storage layer would include:

-   5) Large slices of object payload, typically after compression.-   6) Metadata for versions of named objects, which will reference the    payload chunks to allow the full object to be retrieved.

The presently-disclosed transport requires each chunk to have thefollowing naming attributes:

-   -   A Chunk ID which uniquely identifies the chunk and which will        never reference a different payload. In an exemplary        implementation, the Chunk ID must be effectively globally unique        for at least twice the lifetime that the chunk will be retained        or referenced.    -   A Content Hash ID: If the selected hash algorithm is a        cryptographic hash with strong immunity from pre-image attacks,        such as SHA-2 or SHA-3, then the Content Hash ID may also serve        as the Chunk ID. When only used to validate content the hash        algorithm merely has to be resistant to coincidental collisions.        Whether or not the Content Hash ID is used to identify the        chunk, the Content Hash ID is used to validate the content of        transmitted chunks or chunks retrieved from persistent storage.

In an exemplary implementation, the Chunk ID must have a uniformdistribution so that it can efficiently index locally retained chunks onstorage servers. In the preferred embodiment, the Chunk ID is always theContent Hash ID. Cryptographic hash algorithms always provide a uniformdistribution.

A chunk may also have a Name Hash ID. The upper layer (for example, adistributed storage layer) may name some chunks that are used to storethe root of metadata for a version of an object within the storagesystem and may also have a name that can be used to retrieve the chunkobject. The Name Hash ID may be an additional partial identifier forsuch chunks (where the addition of a version identifier is required toform a complete additional identifier).

Distributed Gets and Puts

The common goal for the distributed get and put procedures is to usemulticast datagrams sent using unsolicited bandwidth to negotiate amulticast rendezvous transfer using solicited bandwidth.

The first step is for the Client (User Client) to initiate thetransaction by multicasting a request to the Negotiating Group. To put achunk, the request that is multicast is a Multicast Put Proposal. To geta chunk, the request that is multicast is a Multicast Get Request.

Each of the recipients of this multicast request then responds to theClient (Chunk Sink for a get, or Chunk Source for a put). When getting achunk, the response is a Get Response. When putting a chunk, theresponse is a Chunk Put Accept. Note that, for Multicast Get Requests,the Chunk Sink must accept each transfer from a specific source.

Once the rendezvous is negotiated, a multicast payload delivery can beinitiated at the negotiated time. In either case (get or put), therendezvous is to a multicast group, referred to herein as the RendezvousGroup. In an exemplary implementation, the Rendezvous Group is specifiedby the Client (Chunk Sink or Chunk Source). When getting a chunk, theRendezvous Group will typically contain only the Chunk Sink, but mayinclude other storage servers seeking to create additional replicas bypiggy-backing on the delivery to the Chunk Sink. When putting a chunk,the Rendezvous Group is a subset of the Negotiating Group.

Lastly, when putting a chunk, a transaction closing acknowledgement isrequired. Note that the upper layer (for example, the distributedstorage layer) which uses the disclosed Replicast transport layer isresponsible for determining whether sufficient replicas have beencreated for a put transaction to complete, or whether the puttransaction should be retried.

Also note that, when getting a chunk, the chunk may also be replicatedto a volunteer storage server to provide additional replicas. Thepresent disclosure allows for opportunistic replication of the chunksmost frequently retrieved, thereby optimizing later retrieval of thosesame chunks.

Chunk Put Proposal—Client Consensus

FIGS. 6-8 depict steps of a client-consensus-based procedure forproposing a chunk put to a distributed storage system in accordance withan embodiment of the invention. In this client-consensus variation ofthe distributed put algorithm, each of the Put Accept messages isunicast to the Client (i.e. to the Chunk Source). Thisclient-consensus-based procedure has advantages over the serialtransmission procedure of FIG. 4 and the relayed unicast transmissionprocedure of FIG. 5. In comparison to the serial transmission procedure,congestion on inbound links is avoided. In comparison to the relayedunicast transmission procedure, contention between the relay (put)traffic and get traffic is avoided.

In the illustrations of FIGS. 6-8, we will walk through a sequence ofevents for a put transaction with the client-consensus procedure. Beforethis sequence of events, an upper layer (i.e. a layer above theReplicast transport layer) has already specified apreviously-provisioned multicast Negotiating Group and apreviously-provisioned multicast Rendezvous Group.

In a first step 1 shown, the Client multicasts a “Put Proposal” 1 to theNegotiating Group of Servers. Data fields in exemplary implementationsof a Put Proposal message are described below in relation to FIG. 24.The Switches may make a best effort attempt to deliver a copy 1.1 of thePut Proposal 1 to every member of the Negotiating Group. Note that, asdisclosed in this application, the nodes in aggregate are highlyunlikely to transmit more unsolicited datagrams than the switch andreceiver buffering can accommodate. Therefore, in almost all cases thePut Proposal will be delivered to the entire Negotiating Group.

Each recipient of the Put Proposal generates and sends a response in theform of a “Put Accept” message. In an exemplary implementation, the PutAccept message may be a “Not Now” message or a “Rendezvous Proposal”message. Data fields in exemplary implementations of a Put Acceptmessage are described below in relation to FIG. 25. When generating aRendezvous Proposal response, each server is free to consider itspending work requests, device performance history, and the desirabilityof accepting new content using a wide variety of algorithms. There is noneed for these algorithms to be uniform amongst the servers. In otherwords, multiple different algorithms may be used by the servers. In theillustrated example: the Put Accept 2.1 message sent by a first Serverin the Negotiating Group is a Not Now message; the Put Accept 2.2message sent by a second Server in the Negotiating Group is a RendezvousProposal message; the Put Accept 2.3 message sent by a third Server inthe Negotiating Group is a Not Now message; and the Put Accept 2.4, 2.5,2.6 and 2.7 messages sent, respectively, by a fourth, fifth, sixth, andseventh Servers in the Negotiating Group are Rendezvous Proposalmessages. The Put Accept 2.* (*=1, 2, . . . , 7) messages are receivedby the sending Client (Chunk Source).

FIG. 7 illustrates the next steps in the put process. The Client (ChunkSource) evaluates all of the “Put Accept” responses and determineswhether a “Rendezvous Transfer” is required. For example, if there werealready sufficient replicas of the chunk to be put, then no RendezvousTransfer would be required.

The criteria for “sufficient replicas” can vary with the usage of thepresent invention. For example some users may establish a policy thattheir content should have at least four replicas in at least twodifferent failure domains, while others may simply require threereplicas in three different failure domains. In a preferred embodiment,this flexibility to accommodate differing policies is enabled by makingthese determinations in a callback function to the upper layer.

In the example illustrated, the Rendezvous Transfer 3 (including thechunk payload) is multicast from the Client to the Rendezvous Group,which is a subset of the Negotiating Group. Hence, copies 3.1 of theRendezvous Transfer 3 are shown as being received by each Server in theRendezvous Group. Data fields in exemplary implementations of aRendezvous Transfer message are described below in relation to FIG. 26.In the illustrated example, the first and third storage servers in theNegotiating Group indicated in their Put Accept response that they couldnot accept delivery now (i.e. returned Not Now messages), and thereforedid not join the Rendezvous Group. The remaining storage servers in theNegotiating Group indicated in their Put Accept responses that theycould accept delivery and so became members of the Rendezvous Group.

The recipients of the Rendezvous Transfers 3.1 respond by unicasting aPayload Acknowledgement (“Payload ACK”) message to the Chunk Source.Data fields in exemplary implementations of a Payload ACK message aredescribed below in relation to FIG. 27. In the illustrated example, thePayload ACK 4.1, 4.2, 4.3, 4.4, and 4.5 messages are sent, respectively,by the first, second, third, fourth, and fifth Servers in the RendezvousGroup. The Payload ACK 4.* (*=1, 2, . . . , 5) messages are received bythe sending Client (Chunk Source).

FIG. 8 illustrates the final step in the put process. The clientcollects the received Payload ACKs and forwards them to the NegotiatingGroup in one or more Relayed ACK message. As depicted, a Relayed ACK 5message may be multicast from the Client such that a copy 5.1 of theRelayed ACK message is received by each Server in the Negotiating Group.The Relayed ACK message informs each Server in the Negotiating Group asto which Servers of the Rendezvous Group are to receive the chunk to beput.

Chunk Put Proposal—Cluster Consensus

FIGS. 9-11 depict steps of a cluster-consensus-based procedure forproposing a chunk put to a distributed storage system in accordance withan embodiment of the invention. This cluster-consensus-based procedurehas advantages over the serial transmission procedure of FIG. 4 and therelayed unicast transmission procedure of FIG. 5. In comparison to theserial transmission procedure, congestion on inbound links is avoided.In comparison to the relayed unicast transmission procedure, contentionbetween the relay (put) traffic and get traffic is avoided.

In the illustrations of FIGS. 9-11, we will walk through a sequence ofevents for a put transaction with the cluster-consensus procedure.Before this sequence of events, the upper layers (above the replicasttransport layer) have already specified a previously-provisionedmulticast Negotiating Group and a previously-provisioned multicastRendezvous Group.

In a first step shown, the Client multicasts a “Put Proposal” 1 to theNegotiating Group of Servers. The Switches may make a best effortattempt to deliver a copy 1.1 of the Put Proposal 1 to every member ofthe Negotiating Group. As with the client-consensus example, the PutProposal will typically be delivered to each member of the NegotiatingGroup.

Each recipient of the Put Proposal responds by generating and sending a“Put Accept” message. As shown in FIG. 9, in this cluster-consensusvariation of the distributed put protocol, each of the Put Acceptmessages is multicast to the other members of the Negotiating Group. Aswith the client-consensus variation previously described, each storageserver is free to employ its own algorithm to generate its Put Proposalbased, for example, upon its performance history, work queue depth, andthe desirability of accepting more storage. In the illustrated example:the Put Accept 2.1 message sent by a first Server in the NegotiatingGroup is a Not Now message; the Put Accept 2.2 message sent by a secondServer in the Negotiating Group is a Rendezvous Proposal message; thePut Accept 2.3 message sent by a third Server in the Negotiating Groupis a Not Now message; and the Put Accept 2.4, 2.5, 2.6 and 2.7 messagessent, respectively, by a fourth, fifth, sixth, and seventh Servers inthe Negotiating Group are Rendezvous Proposal messages. Each Server inthe Negotiating Group receives the Put Accept 2.* (*=1, 2, . . . , 7)messages from the other members of the Negotiating Group.

The next steps in the put process are depicted in FIG. 10. Each memberof the Negotiating Group evaluates the Put Accepts 2.* for thetransaction. A consistent procedure may be applied during the evaluationby each member so as to concurrently determine which of them should takea specific action. One of various conventional procedures may be usedfor this purpose. For example, one compatible procedure involveselecting a lead member (the leader) to be the first-listed designatedmember of the Negotiating Group that intends to accept the transfer.When no member intends to accept the transfer, it may be thefirst-listed designated member of the Negotiating Group, even thoughthat member does not intend to accept. However selected, the selectedServer in the Negotiating Group may multicast the Consensus Put Accept 3to the Client. Hence, a copy 3.1 of the Consensus Put Accept 3 is shownas being received by the Client.

As with the Client-Consensus procedure, the selection process mayaccommodate a variety of user policies. The only requirement is that theevaluation procedures on the various members of the Negotiating Group donot derive solutions that conflict with each other. In a preferredembodiment, a callback to the upper layer is used to enable this policyflexibility.

At a specified time, or within a specified window of time, the Clientperforms the Rendezvous Transfer 4 (including sending the chunk payload)to the Rendezvous Group. Hence, a copy 4.1 of the Rendezvous Transfer 4is shown as being received by each Server that is a member of theRendezvous Group.

The final steps of the put process are depicted in FIG. 11. Eachrecipient of the Rendezvous Transfer 4.1 multicasts a Payload ACK 5.1message to the Rendezvous Group. In addition, the previously-selectedleader of the Rendezvous Group unicasts a Consensus ACK 6 message to theClient.

Chunk Put Proposal with Deduplication—Client Consensus

FIGS. 12 and 13 depict steps of a client-consensus-based procedure forproposing a chunk put to a distributed storage system withde-duplication in accordance with an embodiment of the invention.

The steps shown in FIG. 12 are similar to the steps discussed above inrelation to FIG. 6. However, the system of FIG. 12 has de-duplication,and the chunk to be put is already stored on a number of storage serversin the illustrated example. In particular, the chunk to be put isalready stored on the second, third, fifth, sixth and seventh Servers.Hence, the second, third, fifth, sixth and seventh Servers respond tothe Put Proposal 1.1 with Put Accept messages (2.2, 2.3, 2.5, 2.6 and2.7, respectively) that indicate that the chunk to be put is “AlreadyStored” at that server.

The Client (Chunk Source) receives the Put Accept 2.* (where *=1, 2, 3,. . . , 7) messages. From the number of “Already Stored” responses amongthe Put Accept messages, the Client is able to determine, in thisexample, that the chunk to be put is already stored on a sufficientnumber of storage servers. Hence, in this case, no rendezvous transferis required. Since no rendezvous transfer is required, the Client maysend a Relayed ACK 3 message to the members of the Rendezvous Group, asdepicted in FIG. 13. The Relayed ACK message indicates to the members ofthe Rendezvous Group that there were sufficient replicas already stored,so no new replicas need to be created.

Chunk Put Proposal with Deduplication—Cluster Consensus

FIGS. 14 and 15 depict steps of a cluster-consensus-based procedure forproposing a chunk put to a distributed storage system withde-duplication in accordance with an embodiment of the invention.

The steps shown in FIG. 14 are similar to the steps discussed above inrelation to FIG. 9. However, the system of FIG. 14 has de-duplication,and the chunk to be put is already stored on a number of storage serversin the illustrated example. In particular, the chunk to be put isalready stored on the second, third, fifth, sixth and seventh Servers.Hence, the second, third, fifth, sixth and seventh Servers respond tothe Put Proposal 1.1 with Put Accept messages (2.2, 2.3, 2.5, 2.6 and2.7, respectively) that indicate that the chunk to be put is “AlreadyStored” at that server.

Each Server of the Negotiating Group receives the Put Accept 2.* (where*=1, 2, 3, . . . , 7) messages. In this example, from the number of“Already Stored” responses among the Put Accept messages, each Server isable to determine independently that the chunk to be put is alreadystored on a sufficient number of storage servers such that no rendezvoustransfer is required. In this case, the leader may transmit a ConsensusPut Accept 3 which is received (as Consensus Put Accept 3.1) by theClient (Chunk Source), as depicted in FIG. 15. The Consensus Put Accept3.1 indicates to the Client that there were sufficient replicas alreadystored, so no new replicas need to be created.

Chunk Get—Client Consensus

FIGS. 16 and 17 depict steps of a client-consensus-based procedure forrequesting a chunk get from a distributed storage system in accordancewith an embodiment of the invention. Before this sequence of events, anupper layer (i.e. a layer above the Replicast transport layer) hasalready specified a previously-provisioned multicast Negotiating Groupand a previously-provisioned multicast Rendezvous Group.

Note that, for a chunk get transaction, the specified Rendezvous Groupis one that has been joined by the Client, or an agent acting on behalfof the Client. Typically, the Client (or its agent) will have previouslyjoined several provisioned Rendezvous Groups for previous transactionsand so one of these previously-joined Rendezvous Groups may bespecified.

As depicted in FIG. 16, the Client may multicast, in step 1, a GetRequest 1 to the Negotiating Group. The Switches of the system thenforward the Get Request 1.1 to Servers that are members of theNegotiating Group.

Each Server in the Negotiating Group then generates and unicasts a GetResponse to the Client in response to the Get Request 1.1. This responsemay be generated using an algorithm that factors in the current workqueue depths, the performance history of the devices to be used, andother factors to derive its best estimate of earliest delivery time.However, there is no requirement that this algorithm be uniform acrossall storage servers. In other words, multiple different algorithms maybe used by the storage servers. In the illustrated example: Get Response2.1 is unicast by the first Server; Get Response 2.2 is unicast by thesecond Server; Get Response 2.3 is unicast by the third Server; . . . ;and Get Response 2.7 is unicast by the seventh Server. The Get Responses2.* (where *=1, 2, 3, . . . , 7) are received by the Client.

The Client analyzes the Get Responses 2.* to determine which Servercorresponds to the best response. As shown in FIG. 17, the Client thenmulticasts a Get Accept 3 to the Negotiating Group. The Get Accept 3specifies which Get Response will be accepted (i.e. which Server isselected to provide the chunk). Each Server in the Negotiating Groupreceives a copy 3.1 of the Get Accept 3. Upon receiving the Get Accept,the selected Server may initiate a multicast Rendezvous Transfer 4 tothe Rendezvous Group, which in this case consists solely of the Client.The Client thus receives a copy 4.1 of the Rendezvous Transfer 3 and soobtains the desired chunk.

Chunk Get—Cluster Consensus

FIGS. 18 and 19 depict steps of a cluster-consensus-based procedure forrequesting a chunk get from a distributed storage system in accordancewith an embodiment of the invention. Before this sequence of events, anupper layer (i.e. a layer above the Replicast transport layer) hasalready specified a previously-provisioned multicast Negotiating Groupand a previously-provisioned multicast Rendezvous Group.

Note that, for a chunk get transaction, the specified Rendezvous Groupis one that has been joined by the Client, or an agent acting on behalfof the Client. Typically, the Client (or its agent) will have previouslyjoined several provisioned Rendezvous Groups for previous transactionsand so one of these previously-joined Rendezvous Groups may bespecified.

As depicted in FIG. 18, the Client may multicast, in step 1, a GetRequest 1 to the Negotiating Group. The Switches of the system thenforward the Get Request 1.1 to Servers that are members of theNegotiating Group.

In response to the Get Request 1.1, each Server generates and multicastsa Get Response to the other Servers in the Negotiating Group. Thisresponse may be generated using an algorithm that factors in the currentwork queue depths, the performance history of the devices to be used,and other factors to derive its best estimate of earliest delivery time.However, there is no requirement that this algorithm be uniform acrossall storage servers. In other words, multiple different algorithms maybe used by the storage servers. In the illustrated example: Get Response2.1 is multicast by the first Server; Get Response 2.2 is multicast bythe second Server; Get Response 2.3 is multicast by the third Server; .. . ; and Get Response 2.7 is multicast by the seventh Server. EachServer in the Negotiating Group receives the Get Responses 2.* (where*=1, 2, 3, . . . , 7) from the other Servers in the Negotiating Group.

Each Server in the Negotiating Group analyzes the Get Responses 2.* todetermine which Server corresponds to the best response. As shown inFIG. 19, the one Server that corresponds to the best response initiatesa multicast Rendezvous Transfer 3 to the Rendezvous Group, which in thiscase consists solely of the Client. The Client thus receives a copy 3.1of the Rendezvous Transfer 3 and so obtains the desired chunk.

Chunk Get—Cluster Consensus with Additional Target

FIGS. 20 and 21 depict steps of a cluster-consensus-based procedure forrequesting a chunk get from a distributed storage system where anadditional target is requested in accordance with an embodiment of theinvention.

As depicted in FIG. 20, the Client may multicast, in step 1, a GetRequest 1 to the distributed storage system. The Switches of the systemthen forward the Get Request 1.1 to Servers that are members of theNegotiating Group.

In response to the Get Request 1.1, each of the Servers generates andmulticasts either a Get Response to the other Servers in the NegotiatingGroup. In the illustrated example: Get Response 2.1 is multicast by thefirst Server; Get Response 2.2 is multicast by the second Server; GetResponse 2.3 is multicast by the third Server; . . . ; Get Response 2.6is multicast by the sixth Server; and Get Response 2.7 is multicast bythe seventh Server. In this case, the Get Response 2.7 from the seventhServer is an Additional Target Request 2.7.

The Additional Target Request 2.7 is a request for the seventh Server beadded to the Rendezvous Group. Hence, the Additional Target Requestcreates an additional replica by “piggy-backing” on a get transactionusing the client-consensus procedure. The Additional Target Request 2.7may be generated by the seventh Server because it does not currentlyhave a copy of the requested chunk. In other words, the AdditionalTarget Request is effectively a Get Response that tells the othermembers of the Negotiating Group that this storage server cannot respondto this get request, but would like to do so in the future, so it willbe subscribing to the Rendezvous Group to get a replica of the chunk.

Each Server in the Negotiating Group receives the Get Responses(including Additional Target Requests) 2.* (where *=1, 2, 3, . . . , 7)from the other Servers in the Negotiating Group. Each Server in theNegotiating Group analyzes the Get Responses (including AdditionalTarget Requests) 2.* to determine which Server corresponds to the bestresponse. As shown in FIG. 21, the one Server that corresponds to thebest response initiates a multicast Rendezvous Transfer 3 to theRendezvous Group, which in this case consists of the Client plus theseventh Server. The Client and the seventh Server thus each receives acopy 3.1 of the Rendezvous Transfer 3 and so obtains the desired chunk.

Exemplary Encoding Structures

This section will describe an exemplary set of packets that are onepossible encoding of the operations described herein. The examples shownassume use of actual L3 multicast addresses.

FIGS. 22 and 23 depict a possible encoding of a generic “Replicast”message over L2 frames. As shown, each L2 frame may contain the standardL2 Header, L3 Header and L4 Header. Typically, these may be Ethernet, IPand UDP headers.

The Message (Msg) Sequence number would identify a unique message withinthe context of a source. The source would be identified by the L3 and L4source addresses. Multipathing could associate multiple source addressesinto a multipath session, but this association would not typically bere-iterated in each L2 frame.

The Fragment # indicates which L2 frame of the total sequence within amessage this is. For the first fragment the following attributes wouldbe encoded:

-   -   The total number of fragments.    -   The Message Type.    -   The Message Length

The Message Payload would then be encoded over multiple L2 frames, eachwith incrementing Fragment #s. In accordance with an embodiment of theinvention, the Message Payload may comprise a fragment of a “Replicast”protocol message as described herein.

Finally, in the last fragment, a validator (Msg Checksum) would beincluded covering the entire Msg Payload, including portions deliveredas Unsolicited payload as part of the setup command. This may be aCRC-32c checksum or better. Including a “Layer 5” checksum is aprotection against incorrectly ordered fragments. L2 and L4 alreadyprovide protection against corrupt transmissions.

In some embodiments of the present invention, a Msg Checksum may coveronly the metadata fields because the Content Hash Identifier alreadyvalidates the payload.

As shown in FIG. 22, the Payload of the Unreliable Datagram may includea transaction identifier (transaction ID). The transaction ID mayinclude sub-fields that indicate: 1) whether the message is a request,response or notification (Request/Response/Notification); 2) the sourceof the request or notification (Request/Notification Source); 3) atransaction sequence number (Transaction Sequence #); and 4) asub-sequence number (Sub-Sequence #). The payload may further include anindication of which fragment of the message payload is being carried(This is Datagram #N). Finally, the payload includes the Nth fragment ofthe message payload.

As further shown in FIG. 22, the Payload of the Unreliable Datagram alsoincludes the “Nth fragment of Message Payload.” In accordance with anembodiment of the invention, the Message Payload may be a Replicastmessage. An exemplary encoding structure for a generic Replicast messageis shown in FIG. 23. Note that the exemplary encoding structure of FIG.23 may be, in effect, inserted into the Nth Fragment of Message Payloadfield of FIG. 22.

The structure shown in FIG. 23 includes the following fields: a firstfield that indicates the opcode or message type; a second field thatindicates that total number of fragments in the message; and a thirdfield that is message type dependent. As a couple of examples, theopcode or message type may indicate whether the message is a chunk putproposal, or a chunk put accept. Other message types may be indicated,of course. The Message Type Dependent field (i.e. the third field)includes sub-fields that depend on the message type (i.e. the firstfield).

Exemplary message types are described below. These message typesinclude: Put Proposals (FIG. 24); Put Accepts (FIG. 25); RendezvousTransfers (FIG. 26); Payload ACKs and NAKs (FIG. 27); Get Requests (FIG.28); and Get Responses (FIGS. 29 and 30).

Put Proposals

A Multicast Chunk Put Proposal would have source addresses for L2through L4 reflecting the network interface being used to send themessage. The L3 destination address would be the Multicast Address ofthe Negotiating Group (typically from the Distributed Hash AllocationTable). The L4 destination port would be a port number assigned for useby this protocol either by a local network administrator or a numberingauthority such as IANA (Internet Assigned Numbering Authority).

FIG. 24 depicts exemplary encoding structures for chunk put proposalmessages in accordance with an embodiment of the invention. Theexemplary encoding structure on the left shows a structure for a namedChunk Put Proposal message, while the exemplary encoding structure onthe right shows a structure for an unnamed Chunk Put Proposal message.For example, in Nexenta's Cloud Copy on Write™ object storage system(which will be commercially available from Nexenta Systems of SantaClara, Calif.), a Named Chunk may correspond to a “version manifest”chunk, and an Unnamed Chunk may correspond to a content chunk. Note thatthese structures may be, in effect, inserted into the Message TypeDependent field of FIG. 23.

A multicast Chunk Put Proposal may provide at least the followinginformation:

-   1) The Source of the Chunk Put Proposal. This may be a network    address currently assigned to the port or a permanent identifier of    the server independent of current network assigned addresses. (See,    for example, the source addresses in the L2 through L4 headers of    FIG. 22.)-   2) A Proposal sequence number that will be incremented for each    Chunk Put Proposal sent by a given source. As with all sequence    numbers used in networking protocols, it must have sufficient span    than the vast majority of sequence numbers are not currently in use.    (See, for example, the “Transaction Sequence #” and “Sub-Sequence #”    fields of FIG. 22.)-   3) An Identifier of the target Negotiating Group. (See, for example,    Target Negotiating Group in FIG. 24.)-   4) An enumerator specifying the Type of Chunk Put. This enumerator    is not intended to be meaningful to the transport layer, only to the    storage layer. For example, with Nexenta's Cloud Copy on Write™    object storage system (which is commercially available from Nexenta    Systems of Santa Clara, Calif.), the types may be Payload Chunks,    Sub-manifests and Version Manifests. (See, for example,    Opcode/Message Type in FIG. 23.)-   5) The Content Hash ID for the chunk. (See Chunk Hash ID field in    FIG. 24.)-   6) If this is a Named Chunk, the Name Hash ID. (See, for example,    Bucket Hash ID, Name Hash ID, and Unique Version Identifier under    the Named Chunk Put Proposal Message in FIG. 24.)-   7) The total length of the compressed payload that will be put.    (See, for example, “Length of non-volatile content” in FIG. 24.)-   8) The total length of the above content that will be put    immediately using unsolicited bandwidth, typically in an optional    portion in this message. (See, for example, “Length of above    included in the Put Proposal message” in FIG. 24.)-   9) The multicast address for a Rendezvous Group that will be used to    put the payload. The members of the Rendezvous Group are not    specified because they have not been selected yet. (See, for    example, the “Delivery Group” in FIG. 24.)-   10) The maximum desired delivery rate. This would typically be    expressed as the total bandwidth required, e.g. bits or bytes per    second rather than messages per second. (See, for example, the    Maximum Delivery Rate in FIG. 24.)

In the typical case, where a portion of the payload will be deliveredusing bandwidth from a Reserved traffic class, each recipient of theChunk Put Proposal will respond with a Chunk Put Accept.

Put Accepts

A Put Accept is preferably addressed to the Multicast Address of theRendezvous Group. An embodiment of the present invention may allow a PutAccept to be unicast addressed to the request sender.

FIG. 25 depicts exemplary encoding structures for chunk Put Acceptmessages in accordance with an embodiment of the invention. (Note that a“Put Accept” message may also be referred to herein as a “Chunk Accept”message.) The exemplary encoding structure on the left shows a structurefor a Put Accept message that provides a Proposed Rendezvous. Theexemplary encoding structure in the middle shows a structure for a PutAccept message that indicates Content Already Stored (for systems withdeduplication). The exemplary encoding structure in the middle shows astructure for a Put Accept message that indicates Not Now. Note thatthese structures may be, in effect, inserted into the Message TypeDependent field of FIG. 23.

A multicast chunk Put Accept message may encode the followinginformation:

-   1) The identity of the Multicast Chunk Put Proposal it is responding    to: the source identifier of the request and the sequence number    from that request. (See, for example, the Copy of Put Proposal ID in    FIG. 25.)-   2) The Target Negotiating Group as specified in the original put    proposal. (See, for example, the Target Negotiating Group in FIG.    25.)-   3) One of the following three responses:    -   a) Chunk already stored. (See, for example, the Chunk Accept        Message—Content Already Stored structure in middle of FIG. 25.)        In this case, redundant transmission of the chunk payload is not        required.    -   b) Put Proposal Not Accepted. (See, for example, the Chunk        Accept Message—Not Now structure on right of FIG. 25.) In this        case, the additional payload may also indicate the earliest time        when this Storage Server would want to consider a retry request.    -   c) Put Proposal Accepted. (See, for example, the Chunk Accept        Message—Proposed Rendezvous structure on left of FIG. 25.) In        this case, the additional payload may preferably indicate a time        window and data rate reserved for this delivery.

The upper layer will be responsible for processing these responses todetermine whether the transfer is required and if so what the membershipof the Rendezvous Group should be. For example, the acceptance criteriafor an “adequate” number of Accepts (such that a transfer is performed)may be that at least one of the acceptances is from one of the“designated” servers and that a total number of servers in theRendezvous Group is equal to (or greater than) a desired replicationcount. The Chunk Source may then initiate a multicast RendezvousTransfer to the Rendezvous Group at the consensus time.

Rendezvous Transfers

FIG. 26 depicts exemplary encoding structures for rendezvous transfermessages in accordance with an embodiment of the invention. Thestructures depict a Rendezvous Transfer message without (on the left)and with (on the right) an Arbitrary Chunk ID.

A multicast Rendezvous Transfer message may encode the followinginformation:

-   1) The Rendezvous Group which may be provided in the “Target    Delivery Group” field.-   2) The list of Server IDs that should be in the Rendezvous Group. A    recipient that is not in this list should leave the Rendezvous    Group. This list may be provided in the “List of Delivery Group    Members” field.-   3) The Content Hash ID of the chunk being put. This may be provided    in the “Content Hash ID of Chunk” field. In one implementation, the    Content Hash ID may be used to identify the Chunk.-   4) The Chunk ID, if different from the Content Hash ID. This may be    provided in the “Arbitrary Chunk ID” field.-   5) The delivery rate that is planned. A recipient that does not    believe it can sustain this rate should leave the Rendezvous Group    and explicitly negatively acknowledge the delivery of the chunk    (i.e. explicitly indicate that the chunk was not delivered). The    delivery rate may be provided in the “Delivery Rate” field.-   6) A set of Authentication Tokens for this Chunk. In the context of    a new Chunk Put transaction, there will be exactly one    Authentication Token. Interpretation and usage of the Authentication    Token is not the responsibility of the replicast transport layer.    The Authentication Tokens may be provided in the “Remaining Content”    field, and the length of these tokens may be provided in the “Length    of Tracking Tokens” field.-   7) The remaining payload that was not included as unsolicited    payload in the original Chunk Put Proposal. This may be provided in    the “Remaining Content” field.

Each recipient of the Rendezvous Transfer that is part of a puttransaction will either acknowledge successful receipt and processing ofthe entire chunk with a Payload Acknowledgement (Payload ACK) message,or negatively acknowledge receipt (i.e. indicate failed reception) witha Payload Negative Acknowledgement (Payload NAK). A Payload ACK (or NAK)is also generated in response to a Put Proposal that included an entirechunk payload.

In an exemplary implementation, processing of a received chunk by theupper layer must be complete before the Payload ACK is transmitted. Inaddition, the received chunk must be persistently stored, or applied andthe results persistently stored, before a Payload ACK is sent.

In an exemplary implementation, the Payload ACK may be sent both to theData Source and to a multicast group of all servers that wish to trackthe existence of chunks mapped by a row of the Distributed HashAllocation Table. Such a group may be a specific member of the MulticastAddress Set or may be the default multicast address for the NegotiatingGroup.

An alternative method is to have each recipient of the Chunk Put messagesend just a unicast Payload ACK to the Chunk Source. The Chunk Sourcethen prepares Relayed ACK messages summarizing one or more receivedPayload ACKs; these messages are sent to the appropriate multicastgroup.

The destination group may be the Negotiating Group itself, or it may bea companion multicast address taken from the Multicast Address Set forthe Distributed Hash Allocation Table row where that member isdesignated for Payload ACK messages, either in general or specificallyfor named chunks.

Payload ACKs and NAKs

FIG. 27 depicts exemplary encoding structures for payloadacknowledgement messages in accordance with an embodiment of theinvention. Structures for named and unnamed Payload ACK messages aredepicted on the left and right, respectively. A structure for a PayloadNAK message is depicted in the middle.

The Payload ACK and NAK messages may encode the following information:

-   -   The Chunk ID that is being acknowledged. In an exemplary        implementation, the Chunk ID may be provided in the “Content        Hash ID” field, where the Content Hash ID is generated by        applying a hash function to the content of the Chunk.    -   If these are implemented, the Name Hash identifier and Unique        Version ID for this Chunk. The Name Hash identifier may be        implemented as shown in a combination of the “Bucket ID” and        “Name Hash ID” fields. The Unique Version identifier may be        implemented in the “Unique Version Identifier” field.    -   The status: successful or not. The status may be provided in by        the Opcode/Message Type shown of FIG. 23. If the status is        unsuccessful, then a specific payload NAK error code may be        provided. (See, for example, the Specific Payload NACK Error        Code in the Payload NAK Message shown in FIG. 27.) Indicating        specific reasons for a negative acknowledgement is useful for        diagnostic purposes, but is not necessary for the functionality        of the present invention.    -   When successful, the Server ID that now has this chunk stored.        The Server ID may be a network address currently assigned to the        port or a permanent identifier of the Server independent of        current network assigned addresses. In an exemplary        implementation, the source address or identifier may be provided        in the Request/Notification Source header field in FIG. 22.

When the Payload ACK was only unicast to the Data Source, the DataSource must multicast a Relayed ACK to the Negotiating Group to informthe members of the group of which servers now have this chunk stored.The Data Source may aggregate multiple Payload ACKs for the same chunkinto a single Relayed ACK message.

Get Requests

FIG. 28 depicts exemplary encoding structures for get request messagesin accordance with an embodiment of the invention. Structures for namedand unnamed Chunk Get messages are depicted on the left and right,respectively.

The multicast Chunk Get messages may encode the following information:

-   1) Identification of the transaction:    -   a) A Source ID of the Client or its agent. This may be a network        address currently assigned to the port or a permanent identifier        of the Client (or its agent) independent of current network        assigned addresses. In an exemplary implementation, the source        address or identifier may be provided in the        Request/Notification Source header field in FIG. 22.    -   b) A transaction sequence number. For example, the transaction        sequence number may be provided in the “Transaction Sequence #”        and “Sub-Sequence #” fields of FIG. 22.-   2) Identification of the chunk desired. Depending on the application    layer this may take multiple forms. This could be any of the    following:    -   a) The exact Chunk ID of any chunk that does not have a Name        Hash ID. This Chunk ID will typically have been obtained from a        metadata chunk that did have a Name Hash ID. The exemplary        Unnamed Chunk Get Message shows this case where the chunk is        identified by the “Content Hash ID” field in FIG. 28.    -   b) The exact Name Hash ID of an Object combined with an optional        specification of a desired version. The exemplary Named Chunk        Get Message shows this case where the chunk is identified by a        combination of the “Bucket Hash ID”, “Name Hash ID” and “Unique        Version Identifier Range” fields in FIG. 28.-   3) The Rendezvous Group for this Get Request. This corresponds to    the “Delivery Group” field in FIG. 28.-   4) The maximum amount of unsolicited content that may be delivered    in each response. This corresponds to the “Maximum Immediate Content    Size per Get” field in FIG. 28.-   5) A Reception Window when the client will be ready to receive the    response. This may be the same (or very similar) information as    provided in the Put Accept message. This corresponds to the    “Reception Window” (or “Reception Window(s)”) field in FIG. 28.-   6) A maximum number of auxiliary responses that may be generated for    this request. Once a storage server is acknowledged as the responder    for this request, it may issue Get requests for up to this many    chunks referenced by the main requested chunk. For each of these    allowed auxiliary responses a separate reception window may be    specified. If not specified the delegated get requests will perform    a put transaction to the Rendezvous Group as though it were a    Negotiating Group. This corresponds to the “Maximum # of Delegated    Gets” field in FIG. 28.-   7) Optional additional reception windows that can be used for    auxiliary responses.

In the typical case there will be no Additional Target Requestsgenerated. We will therefore first discuss the multicast Get Requestwithout any having been generated, and leave for later the discussion ofthe case where additional targets are requested.

For a Get Request which specifies delivery immediately or relativelypromptly (as defined by system-wide configuration), each Storage Serverin the Negotiating Group possessing the chunk requested will attempt torespond to the Get Request as soon as its internal work queues allows itto. However, in accordance with an embodiment of the invention, only thefirst responding Storage Server will actually completely respond anddeliver the requested chunk. As disclosed herein, the mechanisms toensure that only one response is generated for each Get Request aredependent on the protocol used to implement this collaboration.

Note that an embodiment of the present invention may also define aUnicast Get Request, in addition to a multicast Get Request. The UnicastGet Request would be a Get Request sent to a specific storage server. Itis anticipated that such a capability may be largely used for diagnosticpurposes, as that there would be no end-user advantage to requesting achunk be delivered by a specific storage server.

Each designated storage server will attempt to respond to a multicastGet Request with a Get Response message. The Get Responses will becollected either by the client or by the Negotiating Group, resulting ina single source being selected.

Get Responses

FIG. 29 depicts exemplary encoding structures for get response messagesin accordance with an embodiment of the invention. Structures for namedand unnamed Get Response messages are depicted on the left and right,respectively.

The Get Response messages may encode the following information:

-   1) A Timestamp indicative of when the response would occur. See    “Timestamp when response would occur” field in FIG. 29.-   2) The Source ID and IP address of the responding server. The Source    ID may be provided in the “ID of storage server” field in FIG. 29.    The IP address of the responding server may be provided in the IP    header of the packet.-   3) Identification of the Multicast Get Request that is being    responded to, and which portion of the response this is: the primary    content; or the ordinal offset of which referenced chunk is being    transferred. The Get Request may be provided in the “Copy of Get    Request ID” field in FIG. 29.-   4) The Rendezvous Group ID that will be used (which is repeated from    the Get request). This may be provided in the “Delivery Group” field    in FIG. 29.-   5) The rate at which the chunk will be transmitted. This may be    provided in the “Delivery Rate” field in FIG. 29.-   6) The Content Hash ID of the chunk it will deliver, and if this is    a named Chunk, the Name Hash ID and unique version identifier of the    chunk. The Content Hash ID may be provided in the “Content Hash ID”    field in FIG. 29. The Name Hash ID and unique version identifier may    provided in the “Bucket ID,” “Name Hash ID” and “Unique Version ID”    fields for the Named Chunk Get Response Message in FIG. 29.-   7) If the requested chunk is too large, an error message may    indicate this problem and specify the actual metadata and payload    lengths (see below description of an error Get Response message).    Otherwise, any immediate portion of the requested content and the    length of the immediate portion may be provided in the “Immediate    Content” and “Immediate Content Length” fields in FIG. 29. Note that    the entire content requested may consist of: a) the metadata and    integrity checking data; and b) the payload. The “Content Length”    field in FIG. 29 may indicate the combined length of the entire    content requested.

In some embodiments, a storage server may respond with a Content NotImmediately Available message that indicates that it cannot return thecontent requested until at least a specified time. This would typicallybe due to migration of the requested chunk to offline storage. Issuingsuch a response may indicate that the process of moving the requestedchunk back to online status has been initiated. However, the requestshould be re-issued at some time after the time indicated.

In an exemplary implementation, each respondent only sends the firstdatagram in the response. This response is sent using unsolicitedbandwidth. The balance will only be transferred once the specific serverhas been selected to perform the rendezvous transfer using reservedbandwidth.

Unless the entire response fits in a single datagram, a single respondermust be selected to complete the transfer. This may be the primarymember of the Negotiating Group offering to deliver the content. Thisselection is multicast as a Multicast Get Accept message to theNegotiating Group, and the selected server will then begin the transfer.The selected rendezvous transfer is then initiated using reservedbandwidth by the selected storage server to the Rendezvous Groupspecified in the original Multicast Get Request.

Error Get Response Message

FIG. 30 depicts exemplary encoding structures for an error Get Responsemessage in accordance with an embodiment of the invention. As shown inFIG. 30, an “Error Code for Chunk Get Response Message” may be providedin this error message.

Volunteer Servers

Volunteer Target Servers may issue Additional Target Requests to theNegotiating Group. These messages request that the Volunteer TargetServers be included in the Rendezvous Group as well. When a multicastprotocol is used with IGMP (Internet Group Management Protocol) control,this is actually a notification that the additional target will havealready joined the Rendezvous Group by the rendezvous time. Theadditional target merely has to attempt collection of the rendezvoustransfer, and saving the chunk if it is received successfully with thepayload matching the signature provided. With a multicast protocol notcontrolled by IGMP, the server selected to perform the RendezvousTransfer adds the server to the Rendezvous Group as provided by thatalternate protocol. Again, the target merely has to collect the chunk onthat multicast group, and save the chunk locally if successful. When aunicast chain simulates multicast, the first responding storage servermust add the server to the list. This will result in the same chaineddelivery as described for the put algorithm, except that no Payload ACKmessage is required.

Expedited Limited Joins

The present disclosure describes a method where multiple servers join aRendezvous Group and then depart it for each put transaction. Additionaltargets also join and then depart a Rendezvous Group for each delivery.

The set of servers that is allowed to join these groups dynamically ispreferably restricted to those that already belong to an enablingcluster-wide group. This allows embodiments to bypass potentiallyexcessive overhead associated with normal management plane operations.

When IGMP controls group membership, then during a put transaction anindividual storage server will:

-   7) Join the group after sending a Chunk Put Accept.-   8) Depart the group when the first of the following events occur:    -   a) It sends a Payload Ack for this transaction. Note that any        storage server has the option to conclude that a transfer will        not complete successfully and send a Payload NAK without waiting        for the transfer to complete. Detection of gaps in the sequence        of received datagrams is one reason for reaching this        conclusion.    -   b) It receives a Rendezvous Transfer which does not list the        storage server as a recipient.    -   c) It receiving a Rendezvous Transfer which specifies a transfer        rate in excess of what the storage server estimates it will be        able to sustain.    -   d) It receives a message from that sender that explicitly aborts        the Rendezvous Transfer.

Mechanisms for Reliable Multicast Payload Delivery

Although a multicast protocol is typically perceived as an unreliableprotocol, the number of congestion drops or mis-delivered packets onmost wired LANs is extremely small. Since multicasts still have anon-zero probability of not reaching all of the target servers, theReplicast transport protocol provides mechanisms that add reliability toan inherently unreliable protocol, but without the amount of overhead of“reliable” transport mechanisms, such as TCP/IP. These reliabilitymechanisms are described below under: 1) Chunk Source Responsibilities;2) Distributed, Reliable Chunk Replication; 3) Requirement forKeep-Alive Service; 4) Lower Layer Tranport Protocol; 5) Contention forUnsolicited Bandwidth; 6) Storage Server Queues; and 7) Detection ofNon-Compliant Core Network.

1) Chunk Source Responsibilities

One aspect of the “reliability” of the presently-disclosed Replicasttransport is that it does not depend on the original chunk source toensure that all of the copies are made. The chunk source is onlyresponsible for ensuring that the minimum set of replicas are created(with at least one copy on a designated server) before the transactioncan be declared complete. Once those copies are guaranteed, then controlis returned to the user application that created the object. Morereplicas will be created, as needed, automatically. Replication ofchunks in accordance with the presently-disclosed Replicast transport isan ongoing process that does not necessarily have an end point.

2) Distributed, Reliable Chunk Replication

Now we describe a distributed mechanism for reliability. In an exemplaryimplementation, each of the Chunk copies keeps a list of the designateddestinations for the chunks. (Note that the original source server maybe one of these chunk copies that is not a designated copy.) The size ofthis list is controlled by the replication count for the object, whichcan also vary by object. If any of the destinations does not yet have acopy of the chunk, then the server holding the chunk wants to replicatethe chunk at one or more of the destinations. This distributedreplication is an ongoing responsibility of each chunk server. Thereplication retries are a continuous background task for the storageservers. However, to avoid network congestion, each of the retries maybe done on a random interval basis, analogous to the CSMACD collisiondetection and retry mechanism. In this manner, the replication task maybe spread across many different servers and not left to a single sourceserver.

This proclivity to replicate exists for each storage server regardlessof its retention of a list of known other replicas. Retaining such dataenables optimization of the replication process, but is not necessaryfor its correctness.

This same mechanism for performing replication is used whenever serversjoin or leave the ring of servers. Each chunk server is continuouslyupdating the list of servers that have copies of a chunk. If a ringmembership change occurs, caused by a failed server or a partitionednetwork, there will typically be insufficient replicas of chunkspreviously assigned to the now missing servers. It will then be theresponsibility of all chunk owners to attempt to replicate these chunks.It is not necessary for every server to have an accurate count of thenumber of replicas. If a given server's estimation is low it willattempt to replicate the chunk, and discover that there are sufficientreplicas. Some packets are exchanged, but there is no unnecessaryrendezvous transfer.

In preferred implementations, the multicast addressing is used forpayload delivery as well as for “unsolicited commands” that carry apayload, rather than negotiating for a time to send the payload.Preferred implementations may ensure that the network switch has beenprovisioned so that the bandwidth allocated for storage and“unsolicited” traffic is non-blocking up to a pre-determined limit andthat the network will not experience congestion as long a s the processof reserving payload transmission does not exceed that threshold. Thishelps to ensure that the “unreliable” multicast is actually quitereliable since it does not run the risk of data loss due to networkcongestion.

While all commands and payload transfers may be retried, they can avoidthe need to retransmit by: protecting the storage traffic from generalpurpose traffic not complying with these special rules; limiting thebandwidth for unsolicited transmissions to a provisioned rate; limitingthe bandwidth for reserved transmissions to a provisioned rate; and onlyutilizing the reserved bandwidth in accordance with rendezvousagreements negotiated using unsolicited transmissions.

3) Requirement for Keep-Alive Service

The present disclosure generally assumes the deployment of a keep-aliveservice on the same set of servers. The keep-alive service will promptlydetect the departure or loss of contact with any member and haveprovision for the authenticated joining/re-joining of members. Further,it is assumed that the keep-alive service will determine the round-triptime for each of the storage servers.

4) Lower Layer Transport Protocol

The present disclosure generally assumes a lower layer transport serviceto provide unreliable datagram service with multicast or unicastaddressing. There are also specific congestion control assumptions madeabout the lower layer protocols. The Replicast transport protocol willfunction correctly even if these services are not provided, but mayexhibit undesirable performance characteristics. For example, thepresently-disclosed implementation generally assumes that delivery ofunreliable datagrams will be effectively drop free if the nodes complywith the provisioned bandwidth limits. The throughput could fall belowwhat would be achieved with conventional solutions if this is not true,but errors will still be detected and properly dealt with.

Specifically the lower layer transport is expected to:

a) Utilize a protected L2 capacity, such as would be provided by theIEEE 802.1 Enhanced Transmission Service (ETS). Specifically, insertionof L2 frames for this class of service must not be allowed fromunauthorized sources. L2 frames that are compliant with the negotiatedrate for this traffic class must not be at risk of being dropped forlack of network buffering because of L2 frames submitted for anothertraffic class.

b) Send messages that are each comprised of multiple unreliabledatagrams to a small defined group of target addresses where each framewithin the message is labeled as to which message it is part of andwhich portion of the message the frame encodes. Placement of payloadfrom each unreliable datagram should be possible even when received outof order.

c) Be able to define a multicast Rendezvous Group as a subset of anadministratively configured group. Methods for implementing multicastaddressing include:

i) Native L2 or L3 multicast addressing capabilities. Both IP andInfiniBand support multicast addressing.

ii) Broadcasting messages on a virtual network (VLAN, VXLAN, etc.) whereonly the members of the multicast group have access to the virtualnetwork.

iii) Use of a custom L4 protocol.

d) Be able to define a multicast Rendezvous Group as a subset of anothergroup created by this transport service.

e) Additionally, take other actions to prevent drop of L2 frames due totemporary network congestion, such as IEEE 802.1 Priority Flow Control(also known as “Per Priority Pause”).

Additionally, the receiving stack should be able to discard packets thatare duplicates of content already provided to the storage layer.

On IP networks, both the UDP and SCTP transport layers can be used. UDPis the preferred embodiment because it is simpler. SCTP addsmulti-homing and multi-pathing, but does so at the expense of needing tomaintain reliable associations between SCTP endpoints. On InfiniBandnetworks, the Unreliable Datagram (UD) transport would be the preferredimplementation.

The transport layer is also traditionally responsible for ensuring errorfree delivery. The presently-disclosed technique assigns thatresponsibility to the storage layer, which validates the Content Hash IDon all transfers.

One feature of the disclosed transport layer is to only enable allowedtraffic. L2 frames for the storage traffic class may only be acceptedfrom authorized end stations. To preserve network security, data sourcesmay only create multicast groups whose membership is a subset of apre-existing group. Network administrators frequently must supportmultiple different groups of users, frequently called tenants, on asingle network. The service providers must be able to ensure each tenantthat there their traffic will not be delivered to ports controlled byother tenants. Network administrators typically need to configure portgroups so that network traffic for different tenants cannot mix withoutgoing through a router that enforces filtering rules.

There are three approaches to providing the desired transport services:

a) Use existing multicast protocols such as IP multicasting and theInternet Group Management Protocol (IGMP). This approach has the benefitof being standards based, but may require an implementation to impose aminimum delay before payload transmission to allow for the latencyrequired by the IGMP protocol.

b) Use a custom control plane that is optimized to establish existingdata-plane control data to use multicast addressing and/or VLANs toachieve the desired group forwarding.

c) Use a custom L3 routing protocol to establish the desireddestinations for each packet. The custom L3 routing would dictate whichL3 routers each packet was to be delivered to, and the full set of L2destinations that each router must deliver the packet to.

With the standard IGMP approach, each host may join or leave anymulticast group, identified by a multicast IP address. IP datagrams sentto a multicast IP address will be best effort delivered to all membersof the group.

The IGMP method requires each target to control its membership in eachgroup. The other solutions involve customizing other methods alreadysupported by network elements for delivering frames to a controlled setof destination links. For all of these methods, the sender must firstinvoke a designated module to reconfigure the switch forwarding tablesas required. Methods for implementing this include, but are not limitedto, OpenFlow modules and vendor-specific Switch control plane plugins.

Alternatively, a custom control plane can directly edit existingdata-plane forwarding control data to effectively emulate multicastdelivery with sender or push based control. This solution works when theforwarding elements have updatable behavior. This can include a customcontrol-plane module, such as defined by Arista Networks of Santa Clara,Calif. for their switches, or by the Open source OpenFlow standard.

The first custom control plane method is to define a Port Group on anactual or virtual network switch. Any broadcast message sent on one ofthose virtual ports will be delivered to all other virtual ports of thegroup. Port Groups are typically limited to ports on a single switch.When the ports are on multiple switches, some form of packet or framelabeling is typically required.

One method of doing so is the 802.1 Virtual LAN (VLAN). Ethernet framestagged with a VLAN are only forwarded to ports belonging to that VLANand to switches as needed to reach those ports. Any broadcast messagesent from one of the virtual ports will be delivered to all othervirtual ports in the VLAN.

There are other protocols which that provide the same functionality as aVLAN, but without the limitation on the number of VLANs. One example ofsuch as protocol is the VXLAN (Virtual eXtensible Local Area Network)protocol.

The last method is to define a custom L3 header which that establishesboth the set of L3 routers that this packet must be delivered to, andthen the L2 destinations at each of those destinations.

5) Contention for Unsolicited Bandwidth

The bandwidth reserved for unsolicited transmissions cannot beguaranteed to be adequate for a spike in demand. With the reservedbandwidth there will be at most one participant attempting to transmitto any given target at any given time. However, the capacity reservedfor unsolicited transmissions is based on an estimate, not onreservations. Estimates can be low. Therefore, collision drops arepossible.

The L2 network may be configured to use technique such as Priority FlowControl (PFC) to minimize drops caused by very short over-demand on theunsolicited capacity. Most L2 networks will allow traffic to exceed thereserved rate for unsolicited traffic provided that it does not requiredropping frames from non-storage traffic. These techniques can make raredrops caused by over-subscribing of the unsolicited capacity even morerare, but they cannot totally eliminate the risk.

Therefore, all unsolicited requests are acknowledged. An unansweredrequest is retransmitted. Because each unsolicited request is uniquelyidentified by its source and a sequence number from that source, allrecipients of a retransmitted request can recognize it as one they havepreviously processed (which can happen when it was their response thatwas lost, rather than the original request). Redundant requests can beprocessed by replaying responses from a response cache.

Even with the potential need to retransmit requests and responses, thepresently-disclosed transport protocol can outperform conventionalsolutions using TCP/IP or other reliable point-to-point transports. Aspike in the number of requests would have also produced a spike in thenumber of connection requests in a TCP/IP solution. The TCP/IP SYNrequests (to establish connections) would have failed just as often, andneeded to be retried as well. While the retries would have been from thekernel, rather than the application layer, there would still need to bemore round-trips with a reliable transport.

With the presently-disclosed transport protocol, exchange of unsolicitedmessages requires two messages. With reliable point-to-point transportsthere would need to be three or four packets required to establish thereliable connection, then the exchange of application layer messages,following by an eventual TCP tear-down of the connection.

The network should be configured so that the buffering available forunsolicited requests in both the forwarding elements and the receivingnodes is sufficient for all but the most extreme peaks of traffic.Well-known conventional solutions can make these exchanges just asreliable as reliable transports with less demand on network resources.

The present disclosure also relies upon the Replicast transport layerpacing its upper layer in some manner that limits the aggregate numberof unsolicited datagrams to comply with the available buffering. Themost minimalistic implementation of this is simply applying anAloha-style random back-off for retransmission of unacknowledged requestdatagrams. When network congestion is high more requests will beunacknowledged, which is sufficient information to spread theretransmission over a wider time span. This effectively lowers theaggregate transmission rate.

However, it should be understood that the method used to pace the upperlayer is not constrained to a conventional delay on the transmission ofan already submitted datagram. Embodiments of the present invention mayuse a variety of techniques to refine the estimation of contention forthe unsolicited bandwidth. Furthermore, this pacing information may besimply shared with the upper layer so that the upper layer may selectwhat datagrams it wants to submit. There is no constraint to merely timethe delivery of already submitted datagrams.

6) Storage Server Queues

In an exemplary implementation, the following types of storage trafficmay be treated differently:

a) Messages carrying Commands and Responses would use an Unsolicitedtraffic class and be queued to a short command/response queue on eachStorage Server. Obtaining an Ethernet traffic classes for bothUnsolicited and Solicited storage traffic will not always be feasible.In many embodiments, a single Ethernet traffic class will be usedcombined with assigning UDP port numbers to either Unsolicited orSolicited inbound queues.

b) Messages carrying Solicited Payload could use a Solicited trafficclass and be steered to a payload queue on each Storage Server, or bedifferentiated solely by the destination UDP port number.

7) Detection of Non-Compliant Core Network

The presently-disclosed transport protocol relies on the core network todeliver multicast packets only to the edge links identified by themulticast group as currently tailored. An implementation may monitorthis compliance, preferably independently but possibly as part ofprocessing incoming Ethernet frames. Excessive delivery, such as wouldbe caused by inadequate forwarding tables resulting in excessiveflooding of Ethernet frames out of all non-originating ports, indicatesthat use of the presently-disclosed protocol should be suspended withconventional TOP-like protocols being used instead.

Alternative Implementations and Special Notes

This section describes alternative implementations and other aspects ofthe presently-disclosed transport protocol.

1) Variations in Participation by Negotiating Group Members

The Negotiating Group identifies the set of storage servers that shouldreceive get or put requests for those chunks. However, not all membersof this group need necessarily be equal.

For example, when IGMP is used to control multicast groups, storageservers that have access to a parent VLAN may be allowed to join themulticast group and thereby become an “associate” member of that group.These “associate” members will receive Put Proposals and Get Requests,but they are not relied upon to provide long-term persistent storage ofchunks. They are not on the designated list for the group, and,therefore, will not count towards certain minimal retentionrequirements.

With sender-controlled memberships, these additional members would belisted as special members of the Negotiating Group. This will requirerepresentation in whatever table or datastore used by the upper layersto selected Negotiating Groups.

2) Simulated Multicast Rendezvous

Alternative embodiments may implement a rendezvous transfer usingchained point-to-point transfers. These transfers would still be donewith a nominally unreliable transport, such as UDP/IP or InfiniBandUnreliable Datagrams (UD). To implement a unicast chain delivery, eachstorage server will do the following steps:

a) Initiate a unicast point-to-point transfer (typically UDP/IP) to aport or service indicator on the Client/Agent. The client, or agent,will explicitly send a delivery abort response back to the sender forall but one of the transfers. Delivery of the chunk will be discontinuedwhen an abort is received. Implementations may choose to slightly delaythe second frame of a response to allow any abort message to bereceived.

b) Otherwise, deliver the chunk to the Client/Agent over thepoint-to-point transfer with a Target list consisting solely of theclient/agent.

3) Delegated Get Request

In one embodiment of the present invention, the process of getting anobject is further optimized for distributed object storage systems whichstore metadata for a version of an object separately from the payload.The root chunk of an object (also called the “version manifest” ormetadata) contains references to the chunks/blocks.

In a default embodiment, the issuer of a Get Request would obtain theversion manifest chunk, and then issue Get Requests for the referencedpayload chunks. This pattern is used in both pNFS (parallel NFS) and theHadoop Distributed File System (HDFS).

In an optimized embodiment, the storage server delivering the versionmanifest chunk may originate Get Requests for a specific number of theinitial payload chunks referenced by the version manifest. Theserequests specify the originator of the Get Request as the target byusing the same Rendezvous Group.

Each L5 message for these auxiliary deliveries specifies a sub-sequencenumber that allows the Chunk Sink(s) to determine which payload chunk isbeing delivered. The original Get Request specifies the maximum numberof auxiliary deliveries it will accept and a delivery window for each.

4) Alternative Delivery Patterns

There are several patterns detailed in this disclosure where the sameinformation is relayed to bother the Rendezvous Group and theNegotiating Group. It should be understood that in all cases any of thefollowing implementations are equally valid:

-   1) The information is sent to the Rendezvous Group. The transaction    originator then relays this information to the Negotiating Group    either as an extra message, which may consolidate multiple    responses, or by including this information in the next message it    would send to the same Negotiating Group.-   2) The information is sent to the Negotiating Group, which then    determines what the consensus is before sending a single response to    the Rendezvous Group.-   3) The information is sent to both groups in parallel. This option    is particularly attractive with a custom L3 protocol.-   4) The information is sent to both groups in parallel under specific    scenarios where the implementation has determined that the improved    latency offered by dual forwarding this specific information    justifies the additional network traffic. Such determinations may be    dependent on implementation or even site-specific factors.

5) Alternative Indefinite Reservations

In an alternative embodiment of the present invention, it may beadvantageous to recognize when the storage cluster consists of arelatively small number of storage servers and a similarly small numberof clients.

When this condition is recognized it may be advantageous for storageservers to grant permanent bandwidth reservations to the clients, andcredits for creation of chunks up to a certain aggregate size.

When such a reservation is granted, the clients would be able todispense with making a Put Proposal, simply assume the Rendezvous Groupwas identical to the Negotiating Group and immediately put the chunkusing the unsolicited protocol.

When the number of storage servers increased the system would shift tonormal operations and require the handshake to reserve protocol.

Upper Layer Decision Making

The transport protocol disclosed includes decision making performed bythe upper layer. This is the layer above the transport layer. In oneembodiment, the upper layer is a storage layer.

For get transactions, the upper layer (of the client in a clientconsensus embodiment, or of the servers in the negotiating group in acluster consensus embodiment) is responsible for evaluating all GetResponses to determine which offering server will be the source of thetransfer, and the time of the transfer (within the range offered). Thesource and time of the transfer may then be provided in a Get Acceptmessage. In one simple embodiment, the transfer source may be selectedfrom the offering servers by a randomized selection technique. Inanother embodiment, the transfer source may be selected from theoffering servers by a procedure which takes into account earliest timefor transfer indications obtained via the Get Responses and may alsotake into account the location of the offering servers within thenetwork topology. In one example, offering servers closer to therequesting client in the network topology may be favorably weighted.

For put transactions, the upper layer of the servers in the negotiatinggroup is responsible for evaluating all Put Proposals to determinewhether a rendezvous transfer is needed, and if so, at what time and atwhat rate. The time and rate of the transfer, if needed, may then beprovided in a Rendezvous Proposal message to the initiating client (inthe client consensus embodiment) or to the other servers in thenegotiating group (in the cluster consensus embodiment).

The upper layer is also responsible for determining when each serverwill offer to do a receive or transmit. This determination may startwith the best estimate that the server can make as to the earliest timewhen the server can be confident that the transfer can occur.Determining the best estimate for the earliest time may involvescheduling of network bandwidth on the local links for the server (tofind the earliest time when the link will be free for reception ortransmission of the chunk) and of its input/output to persistent storage(since there is little benefit of receiving data that cannot be writtento disk until much later because other writes are already committedand/or because of required head movement for traditional hard diskdrives).

The algorithm used to make these scheduling estimates may be dependenton the relative speeds of the network and storage devices, and on theresources available to make the estimations. Embodiments of the presentinvention do not necessarily require any specific algorithm beimplemented, although it is preferable that the estimation be as good aspossible with the available resources.

A comparison can be made with a free market system. Approaching anoptimum balancing of supply versus demand is not dependent on everyparticipant analyzing the market perfectly, just that generallyparticipants are trying to optimize their decisions.

Example Computer Apparatus

FIG. 31 depicts a simplified example of a computer apparatus 3100 whichmay be configured as a client or a server in the system in accordancewith an embodiment of the invention. This figure shows just onesimplified example of such a computer. Many other types of computers mayalso be employed, such as multi-processor computers.

As shown, the computer apparatus 3100 may include a processor 3101, suchas those from the Intel Corporation of Santa Clara, Calif., for example.The computer apparatus 3100 may have one or more buses 3103communicatively interconnecting its various components. The computerapparatus 3100 may include one or more user input devices 3102 (e.g.,keyboard, mouse, etc.), a display monitor 3104 (e.g., liquid crystaldisplay, flat panel monitor, etc.), a computer network interface 3105(e.g., network adapter, modem), and a data storage system that mayinclude one or more data storage devices 3106 which may store data on ahard drive, semiconductor-based memory, optical disk, or other tangiblenon-transitory computer-readable storage media 3107, and a main memory3110 which may be implemented using random access memory, for example.

In the example shown in this figure, the main memory 3110 includesinstruction code 3112 and data 3114. The instruction code 3112 maycomprise computer-readable program code (i.e., software) componentswhich may be loaded from the tangible non-transitory computer-readablemedium 3107 of the data storage device 3106 to the main memory 3110 forexecution by the processor 3101. In particular, the instruction code3112 may be programmed to cause the computer apparatus 3100 to performthe methods described herein.

Summary of Features and Advantages of Multicast Transport

The presently-disclosed transport protocol allows the set of storageservers providing persistent storage for a chunk to be selected fromthose that can store the chunk most promptly, rather than arbitrarilyselecting a set of storage servers without regard for network traffic orserver workloads.

In conventional solutions, selecting storage servers based upon theircurrent loads was limited to systems with a centralized metadata system,such as HDFS and pNFS. Other previous solutions use consistent hashingalgorithms to eliminate the central bottleneck, but are then incapableof considering dynamic factors such as queue depth.

The presently-disclosed transport protocol allows the Chunk Source toselect the optimum set of storage servers to take initial delivery of achunk from amongst the Chunk Put Accept responses collected to amulticast Put Proposal. Centralized metadata solutions can only performthis optimization to the extent that the central metadata server isaware of the resource status of every storage server in the cluster.Existing consistent hash algorithms can only adjust boundaries forlonger term changes in the distribution. Any change in the distributionof chunks requires moving previously committed chunks. Only majorchanges in the distribution can justify the migration costs of adjustingthe distribution.

The presently-disclosed transport protocol allows the initial source ofa chunk to select the initial Rendezvous Group. In selecting the initialRendezvous Group, the source server has many options to influence themembers of the group. Some of the considerations may include, spreadingreplicas across failure domains, selecting destinations that have thelargest amount of free space, destinations that have a best rating(combination of CPU power and memory space available, e.g. WindowsExperience Index) as well as other factors that can vary dynamically,including the speed, number and/or cost of the link(s) between thesource and the sink.

The presently-disclosed transport protocol also allows storage serverswith excess capacity and currently low work queues to volunteer toprovide additional replicas of chunks. In fact, many storage systemshave the notion of “hot stand-by” drives that remain powered up, butidle, to step in when an existing drive fails. With an exemplaryimplementation of the present invention, these hot stand-by drives canbe used to perform a performance enhancing “volunteer” duty to holdvolatile extra copies of objects. Clients can find these additionalreplicas using the Negotiating Group. The Negotiating Group also enablescollaboration within the group can be found by clients seeking thosechunks and/or when replication of those chunks is required due to theloss of an existing storage server (or the additional of a new storageserver).

The presently-disclosed transport protocol also allows for dynamicadjustment of a Distributed Hash Allocation Table to dynamicallyload-balance assignment of responsibilities among the storage servers.The present disclosure also allows for alternate strategies, such asholding new servers in reserve to replace failed or to offloadoverloaded servers. Prior solutions could only provide this type offlexible resource assignment by centralizing the function of themetadata server.

The presently-disclosed transport protocol also provides for improvedutilization of network bandwidth and buffering capacities. Bandwidthcapacities may be quoted for network elements as though they werereserved. However, this is not how network elements actually operate.Buffers are not pre-enumerated for different classes of service. Theycome from a common pool. Stating that the network element has a queuefor up to 40 Ethernet frames in Class X does not mean that there are 40buffers pre-allocated for that purpose. Rather, it means that after 40frames are queued for Class X, further frames for Class X may or will bedropped, and that no frames for a different Class that is below itsquota will be dropped because an excessive number of frames for Class Xwere queued.

This can be thought of as a reservoir with controlled ingress and egressrates. As an analogy, it may be known that, in aggregate, 30% of thewater in the reservoir came from river W, but that does not mean that itis easy to find the specific drops in the reservoir.

With an exemplary implementation of the presently-disclosed transportprotocol, the time that copies of a given chunk will be in networkelement buffers is greatly reduced. With unicast protocols, a bufferwill be required for the reception time, queued time and transmit timefor each of the three copies. In contrast, with the presently-disclosedprotocol, a single buffer will only be held for the reception time, thelongest queue time of the three copies, and the transmit time. Whilethis will be more than one-third of the time that buffers will be heldfor the unicast protocols, it is still a considerable improvement with areplication count of three. Higher replication counts produce even moredramatic improvements.

Even if there are no changes in the class of service traffic shaping forany of the Ethernet priorities, this now unused buffer capacity canenable more Unsolicited and more non-storage packets to be successfullydelivered over the same local area network than could have beendelivered had a unicast delivery strategy been used. Less buffering alsomeans prompt transmission, which will improve average delivery times.

In summary, the presently-disclosed transport protocol provides foreffectively reliable delivery of multicast chunks (and associatedtracking data) using unreliable datagrams. It does this by effectivelyeliminating the risk of congestion-based drops. It extends enhanced L2techniques, such as IEEE 802.1 DCB (DataCenter Bridging) protocols, bydynamically allocating edge bandwidth between unsolicited and solicitedtransfers. Each transfer is paced so as to avoid sustainedover-subscription of network capacity, which the L2 techniques such asDCB cannot solve.

II. Scalable Object Storage Using Multicast Transport

In accordance with an embodiment of the invention, an object storagesystem and method uses multicast messaging to perform replication ofchunks that encode object metadata and data within distributed objectstorage systems by using multicast messaging to notify assigned serversand distribute chunk copies for storage and replication. Reliability maybe advantageously achieved by collaboration between thepresently-disclosed object storage layer and the multicast messaginglayer described in detail above.

Metadata and data are frequently handled differently in conventionalsolutions, but there are still fundamental similarities in the handlingof metadata and data. A preferred embodiment of the presently-disclosedobject storage layer handles metadata and data in a unified manner.However, uniform handling is not a necessity for the present invention.In this disclosure, the term “chunk” can refer to any subset of themetadata or data for a version of an object, without regard to howuniform or divergent the handling of metadata is from data in a specificstorage system.

Multicast transmission, which performs the sending of data once to bereceived by multiple receivers, is traditionally viewed as beinginherently unreliable. The presently-disclosed object storage layerprovides effective reliability in collaboration with a transport layeron top of conventional unreliable multicast messaging. Thiscollaboration fulfills the classic role of the transport layer. Thiscollaboration enables avoidance and/or recovery from congestion drops inthe network and also provides for recovery from non-congestion drops aswell.

Conventional multicast transmission is deployed where there can be avery large number of recipients, making normal flow or congestioncontrol unworkable as a solution. In contrast, an embodiment of thepresently-disclosed object storage system anticipates using a smallnumber of recipients (such as, for example, less than one hundredrecipients) so that flow control is manageable. An additional aspect ofthe presently-disclosed object storage system is that due to theredundancy of chunk replicas, the system is safe when a minimum numberof copies have been made, and the storage system can be tolerant ofjittered delivery.

The presently-disclosed object storage system uses multicast addressingto resolve issues such as assigning which storage servers will holdwhich chunks, and then performs a negotiation to select a rendezvoustime window for a subset of the assigned servers. Multicast messaging isthen used to enable efficient, reliable and eventually consistentdistribution of chunks.

Layering

The presently-disclosed object storage system is a distributed objectstorage system that relies on specific multicast messaging capabilitiesbeing provided from a transport layer. However, the separation betweenthe transport layer and the storage layer is not conventional.

These two layers occupy a layer above the conventional transport layer(“L4”) and below the session layer. Other protocol suites occupying thislayer have been referred to as “L5” protocols, even though strictlyspeaking they are below the Session Layer (which is the correctdefinition of Layer 5). The primary examples of “L5” protocol suitesinclude iSCSI and RDMA over IP (iWARP).

The presently-disclosed storage layer relies on a transport layer atthat same layer. Together, the presently-disclosed storage layer and itssupporting transport layer may be referred to as “Replicast”. Theassignment of responsibilities between the presently-disclosed storagelayer and its supporting transport layer is itemized in Table 1 underthe description of the scalable transport.

Distributed Object Storage System that Scales Out

The presently-disclosed object storage system provides a method forstoring and retrieving chunks encoding object metadata and/or objectpayload in a distributed object storage system.

Conventional object storage systems rely upon point-to-point connectionsfor all chunk transfers (ingest, replication or retrieval). In contrast,the presently-disclosed object storage system provides effectivelyreliable access to stored objects built upon unreliable multicastdatagrams. By making multicast effectively reliable, it becomes suitablefor robust ingest, replication and retrieval of data that is organizedinto chunks.

Multicast collaboration allows dynamic collaboration in determiningwhich storage servers are storing specific chunks without requiringcentral or hierarchical control of metadata. Prior object storagesystems have chosen between effectively centralized control of locationassignment and distributed hash algorithms. However, centralized controlof location assignment creates processing bottlenecks that impairscalability of the object storage system, and conventional distributedhash algorithms, while scalable, cannot distribute chunks based ondynamic factors, such as storage server capacity, work queue depths oravailable network bandwidth.

In contrast, the presently-disclosed object storage system providesdistributed control of location selection in a manner that accommodatesdynamic loading of servers when making those decisions. This enables theoptimization of allocation across storage servers for both storagecapacity and dynamic load balancing of the depth of work queues. Hence,the total capacity of the storage cluster, both in terms of TBs(terabytes) of storage and IOPs (input/output operations), can beutilized in an optimized manner even when the cluster has scaled beyondthe control of a single metadata server.

Stateless Retrieval

The same Negotiating Group also enables retrieval of chunks withoutprior knowledge of prior put or replication transactions. Retainingknowledge of prior put or replication transactions in a reliable mannerwould require centralized metadata. Instead, a get request is multicastto the Negotiating Group specifying a multicast Rendezvous Group thatinitially only includes the requesting node as the target of therequested chunk (or chunks for certain compound get transactions, to bedescribed). The only server that must track that it has a specific chunkis the server which holds the chunk.

The multicast messages used to respond to a get request may be verysimilar to those used to put or replicate chunks. They also allow forrapidly pruning the responses from all but the earliest responder to anymulticast get request.

The presently-disclosed object storage layer also enables piggy-backingthe creation of additional replicas on any get request. Additionaltargets can be added to the Rendezvous Group and thereby receive thesame content that was retrieved for the get requester.

Distributed Editing of the Hash Allocation Table

Multicasting also enables distributed editing of the shared HashAllocation Table. This enables more flexible tuning of the mapping ofChunk Hash ID to Negotiating Groups than a conventional distributedhashing scheme would allow.

Some of the strategies enabled in preferred embodiments include:

-   -   Having new storage servers wait to assign themselves ranges of        Chunk Hash IDs based upon failure of other storage servers or        detecting an over-loaded storage server.    -   Failing over shared storage devices from one storage server to        another storage server upon failure of the first storage server.

The above techniques enable specific optimization techniques forobject-oriented storage systems.

The above techniques may be optimized to provide improved latency whenfetching an object stored as a manifest chunk which references multiplepayload chunks where the processing of the manifest get issues the firstseveral chunk get requests directly, specifying the Rendezvous Group ofthe original request. This eliminates the turn-around time required fora client issuing the get for the manifest chunk to issue the get for thereferenced payload chunks itself (or from a broker acting on behalf ofthe client).

Nodes and Network Elements of Object Storage System

The presently-disclosed solution may be implemented using a systemcomprised of:

-   1) A plurality of nodes that store and retrieve chunks. Some nodes    act strictly as clients, and only accept chunks for the purpose of    delivering them to the end client. A subset of the nodes must be    willing to act as Storage Servers to provide persistent storage for    client nodes.-   2) A plurality of network elements connecting the nodes. The    presently-disclosed solution may rely on existing standard protocols    and use them to provide enhanced reliability without requiring    changes to the network stacks of any of the network elements. The    round trip times within this network may be relatively short and    fairly uniform.

The specific congestion control protocol specified herein requires eachnode to take responsibility for managing bandwidth reserved for bulkpayload delivery to that node.

Methods Provided by the Object Storage System

The presently-disclosed object storage system provides: A) methods fordistributing and retrieving chunks using multicast addressing; B)methods for reliable and optimal multicast transmission of chunks bynegotiating rendezvous to reserve a Rendezvous Group for a specifictransmission during a specific time window; and C) methods formaintaining a shared and distributed Hash Allocation Table withoutcentral bottlenecks that could become single points of failure.

A) Methods of Distributing and Retrieving Chunks

The presently-disclosed solution creates a multicast group, named theNegotiating Group, to control both distribution (put) and retrieval(get) of chunks.

Messages may be addressed to either Negotiating Groups and/or toRendezvous Groups. A Rendezvous Group may be a subset of a NegotiatingGroup for a put transaction, or a union of the initiating client and asubset of the Negotiating Group for a get transaction. Specifically, thepresently-disclosed solution discloses the use of a specialized form ofDistributed Hash Table that is a shared and distributed Hash AllocationTable to locate or retrieve the Negotiating Group for a specific chunkin the absence of a central metadata system.

The Hash Allocation Table is used to locate specific chunks in similarfashion to how a Distributed Hash Table would have been used. A Hash IDis used to search for a row in the table, where the Hash ID may havebeen calculated from the chunk or retrieved from metadata. Where theHash Allocation Table differs from a Distributed Hash Table is that themethod for updating the shared Hash Allocation Table is far moreflexible. The method for updating the Hash Allocation Table allowsadditional servers to be added to the table based on either contentalready present in the servers or on a volunteer basis. Thepresently-disclosed solution also allows for servers which are not alsoclients to hold only the subset of the Hash Allocation Table that isrelevant to them.

Each Negotiating Group identifies a subset of the cluster's storageservers that are all of the servers involved in storing or retrieving aspecific chunk. Identification of a subset of the storage servers iscrucial to allowing unsolicited transmission of buffers without priorbandwidth reservations. If the number of potential unsolicited messagesthat a given storage server can receive is too large then buffering inthe network forwarding elements and the receiving end itself will beinsufficient to make delivery of unsolicited messages effectivelyreliable.

In one embodiment, the Negotiating Group is obtained by a lookup in ashared Hash Allocation Table. This table can be identical in structureto a table that implements a conventional distributed hash table,although the Hash Allocation Table preferably has a variable (ratherthan fixed) number of members (servers) designated in each row. The HashAllocation Table differs from a conventional distributed hash table inthat there are numerous methods for populating its rows.

As with a Distributed Hash Table, a chunk's Hash Identifier iscalculated based upon the chunk's name, or the chunk value (payload).The Hash Identifier is used to look up the row(s) that are used to holdthe identities of the servers that are responsible for storing that HashIdentifier. Many methods are well known for performing this type oflookup function.

A negotiation is conducted within the Negotiating Group using unreliabledatagrams sent with multicast addressing, as will be specified later, toselect a subset of those servers that the chunk must be delivered (orreplicated) to.

The presently-disclosed solution requires each chunk to have thefollowing naming attributes:

1) A Chunk ID. The Chunk ID uniquely identifies the chunk and which willnever reference a different payload. It must be effectively globallyunique for at least twice the lifetime that the chunk will be retainedor referenced.

2) A Content Hash ID. Each embodiment of the present invention selects aspecific hash algorithm that all servers in the cluster agree upon. Ifthe selected hash algorithm is a cryptographic hash of the content, suchas SHA-2 or SHA-3, then the Content Hash ID may also serve as the ChunkID. When the Content Hash ID also acts as the Chunk ID, the algorithmselected is preferably strongly resistant to pre-image attacks. Whenonly used to validate content, the hash algorithm merely has to beresistant to coincidental collisions. Whether or not it is used toidentify the chunk, the Content Hash ID is always used to validate thecontent of transmitted chunks or chunks retrieved from persistentstorage.

The Chunk ID should have a uniform distribution so that it can be usedto efficiently index locally retained chunks on storage servers. In apreferred embodiment, the Chunk ID is always the Content Hash ID.Cryptographic hash algorithms generally provide a uniform distribution.In alternate embodiments, the Chunk ID may be supplied as an ArbitraryChunk ID by a centrally controlled metadata system (such as an HDFSnamenode). That metadata system would be responsible for creating ChunkIDs that with a uniform distribution.

A chunk may also have a Name Hash ID. Chunks that are used to store theroot of metadata for a version of an object within the storage systemalso have a name that can be used to retrieve the chunk object. The NameHash ID is an additional partial identifier for such chunks (theaddition of a version identifier is required to form a completeadditional identifier). In a preferred implementation where theseindexes are implemented is a single flat index, entries found using theName Hash ID will contain the Chunk ID while those found with Chunk IDwill specify the local storage locations where the chunk payload isstored and the chunk back-references are tracked.

When working with chunks that have a Name Hash ID it is used to indexthe Hash Allocation Table to retrieve the Negotiating Group.

A1) Distributed Put Operation

The above-described FIGS. 6-15 provide illustrative examples oftransactions to put a chunk to an object storage system in accordancewith the presently-disclosed solution.

The first step in a distributed put operation is for the data source toidentify the Negotiating Group comprised of the set of target storageservers that should receive a Chunk Put proposal for the chunk.

A1a) Identification of the Negotiating Group

The Negotiating Group may be identified through several methods,including the following:

-   -   1. By looking up the Name Hash ID for the chunk in the shared        Hash Allocation Table, or looking up the Content Hash ID in the        same table when the chunk does not have a name. An unnamed chunk        may be identified directly or indirectly from the contents of a        named Chunk. The Negotiating Group row so found would list the        target servers for a range of Hash IDs, and a Multicast Group ID        already associated with this group.    -   2. In alternative implementation, the Negotiating Group may be        identified by a central metadata system, such as a namenode in        the Hadoop Distributed File System (HDFS).

A1b) Chunk Put Proposal

Having selected the set of targets, a Chunk Put Proposal is sent to thisNegotiating Group (Designated Super-Group). A Multicast Chunk PutProposal message may encode at least the following information:

1) An Identifier of the target Negotiating Group.

2) An enumerator specifying the Type of a Chunk Put. These types wouldinclude Payload Chunk, Version Manifest and Chunk Manifest.

3) The Content Hash ID for the chunk.

4) If this is a named chunk (which holds the root of the metadata for aversion of an object), then the name of the object to be put must bespecified. In a preferred embodiment, this includes the Name Hash Id ofthe enclosing Container (commonly referred to as a “bucket”), the NameHash ID and the unique version identifier for the version to be created.

5) The total length of the content that will be put.

6) The total length of the above content that will be put immediatelyusing unsolicited bandwidth, typically in an optional portion in thismessage.

7) The multicast address for a Rendezvous Group that will be used to putthe payload. The members of the Rendezvous Group are not specifiedbecause they have not been selected yet.

8) Other information as required by the transport layer.

A1c) Chunk Put Accept

A Chunk Put Accept message encodes the following information:

1) The identity of the Put Proposal that this is in response to:Requester, Sequence # and sub-sequence #.

2) One of the following three responses:

a) Chunk already stored. Redundant transmission of the chunk payload isnot required.

b) Put Proposal Not Accepted (“Not Now”). The additional payload willindicate the earliest time when this Storage Server would want toconsider a retry request.

c) Put Proposal Accepted. The additional payload will indicate the timewindow and data rate reserved for this delivery.

Dependent on application layer logic, the Data Source will have a policyon the desired number of targets it wants to deliver the chunk to on afirst round. In some cases there will already be enough targets holdingthe chunk that no further deliveries are needed. Otherwise, the DataSource will determine the Rendezvous Group for the payload, which is asubset of the Negotiating Group.

Consider an example with four Data Sinks in a Negotiating Group. In thisexample, three of the Data Sinks may accept the put proposal, while thefourth may indicate that it cannot accept the chunks being put currently(by sending a “Not Now”). Typically, the acceptance criteria for an“adequate” number of Accepts may be that at least one of the acceptancesis from one of the “designated” servers, and there must be a total of“replication count” servers in the rendezvous group.

A1d) Rendezvous Transfer

The Chunk Source will then initiate a Multicast Rendezvous Transfer tothe Rendezvous Group at the consensus time. The mechanisms forimplementing a multicast rendezvous transfer are dependent on thetransport layer.

A1e) Payload ACK

Each recipient of a Rendezvous transfer that is part of a gettransaction will either acknowledge successful receipt of the entirechunk (or negatively acknowledge failed reception) with a Payload ACK. APayload ACK is also generated in response to a Put Proposal thatincluded the entire payload.

Processing of a received chunk by the upper layer must be completebefore the Payload Ack is transmitted. The received chunk must bepersistently stored, or applied and the results appropriately stored,before a Payload Ack is sent. When a storage server is responsible forproviding persistent storage, the results must be persistently storedbefore a Payload Ack is appropriate.

The Payload ACK must be sent both to the Data Source and to a multicastgroup of all servers that wish to track the existence of chunks mappedby a row of the Hash Allocation Table. Such a group may be a specificmember of the Multicast Address Set or may be the default multicastaddress for the Negotiating Group.

An alternative method is to have each recipient of the Chunk Put messagesend just a unicast Payload ACK to the Data Source. The Data Source thenprepares Relayed ACK messages summarizing one or more received PayloadAcks; these messages are sent to the appropriate multicast group.

The destination group may be the Negotiating Group itself, or may be acompanion multicast address taken from the Multicast Address Set for theHash Allocation Table row where that member is designated for PayloadACK messages either in general or specifically for named chunks.

In a preferred embodiment, the Payload ACK encodes the followinginformation:

1) The identity of the Put Proposal that is being completed.

2) The Chunk ID that is being acknowledged.

3) The status: successful or not. Indicating specific reasons for anegative acknowledgement is useful for diagnostic purposes, but is notnecessary for the functionality of the present invention.

4) When successful, the message includes an identifier of the serverthat now has this chunk stored.

When the Payload ACK was only unicast to the Data Source, the DataSource must multicast a Relayed ACK to the Negotiating Group to informthe members of the group of which servers now have this chunk stored.The Data Source may aggregate multiple Payload ACKs for the same chunkinto a single Relayed ACK message.

A1f) Making the Put Transaction Reliable

Finally, the Chunk Source evaluates whether there has been a sufficientset of positively acknowledged deliveries of the chunk. Such adetermination may be more complex than merely checking the number ofdelivered chunk. For example, an embodiment may require that a minimumnumber of the servers that are permanent members of the NegotiatingGroup hold the Chunk. A storage server that offered only volatilestorage might be acceptable as an additional copy, but not one that canbe relied upon. However sufficiency of delivery is evaluated, ifinsufficient replicas have been created, then the Chunk Source and eachsuccessful recipient of the chunk will attempt to put the chunk againafter a random back-off delay.

In one embodiment of this collaboration, each interaction described isencoded as a PDU (Protocol Data Unit) which becomes one or more L2frames. Each PDU is delivered to the set of storage nodes identified bya Multicast Address, whether by a natural Multicast protocol such asmulticast UDP over IP or by cut-through replication using unicastconnections such as TCP over IP.

The decision to use a native multicast protocol or a unicast simulationthereof can be made independently for the control PDUs (Get Request,Chunk Put Proposal, Chunk Put Accept and Payload ACK) and the payloaddelivery PDUs.

In one embodiment, multicast is used for payload delivery and IGMP isused to control membership in the multicast group. In these embodimentseach Data Sink joins the multicast group before the time window acceptedin their Put Accept reply, unless they specifically indicate that theyanticipate the offer will be rejected.

A2) Cluster-Wide Timestamp

The presently-disclosed solution assumes a common timestamp maintainedby all members of the storage cluster. There are several well-knowntechniques for maintaining an adequately synchronized clock over a setof distributed servers, and any of which are suitable for animplementation of the present invention (e.g., Network Time Protocoland/or Precision Time Protocol).

A3) Distributed Get Operation

The above-described FIGS. 16-21 provide illustrative examples oftransactions to get a stored chunk in accordance with thepresently-disclosed solution. In the example shown in FIGS. 20-21, thechunk is also replicated to a volunteer Storage Server to provideadditional replicas. The presently-disclosed solution allows foropportunistic replication of the chunks most frequently retrieved,thereby optimizing later retrieval of those same chunks.

The first step of the distributed get operation is for the client, or anagent acting on behalf of the client, to join a Multicast RendezvousGroup previously provisioned for use by this client. Typically, theclient will have joined several provisioned Rendezvous Groups forprevious transactions and will be selecting one of the groups previouslyused for a completed transaction.

A3a) Multicast Get Request

The client then issues a Multicast Get Request to Negotiating Groupappropriate for the requested chunk. The group is identified just asdescribed for the put procedure.

This Multicast Get Request includes, but is not limited to, thefollowing:

1) Identification of the transaction:

a) A Source ID of the client or its agent.

b) A transaction sequence number.

2) Identification of the chunk desired. Depending on the applicationlayer this may take multiple forms. This could be any of the following:

a) The exact Chunk ID of any chunk that does not have a Name Hash ID.This Chunk ID will typically have been obtained from a metadata chunkthat did have a Name Hash ID.

b) The exact Name Hash ID of an Object combined with an optionalspecification of a desired version.

3) The Rendezvous Group for this Get Request.

4) The maximum amount of unsolicited content that may be delivered ineach response.

5) A Reception Window when the client will be ready to receive theresponse. This is the same information as provided in the Put Acceptmessage.

6) A maximum number of auxiliary responses that may be generated forthis request. Once a storage server is acknowledged as the responder forthis request, it may issue Get requests for up to this many chunksreferenced by the main requested chunk. For each of these allowedauxiliary responses a separate reception window must be specified.

7) Optional additional reception windows that can be used for auxiliaryresponses.

In the typical case, there will be no Additional Target Requestsgenerated. We will therefore complete this description without anyhaving been generated, and discuss additional targets after completingan initial description of the get algorithm.

For a Get Request which specifies delivery immediately or relativelypromptly (as defined by system-wide configuration), each Storage Serverin the Negotiating Group possessing the chunk requested will attempt torespond to the get request as soon as its internal work queues allows itto. However, only the first responding Storage Server will actuallycompletely respond and deliver the requested chunk. The mechanisms toensure that only one response is generated for each Get Request aredependent on the protocol used to implement this collaboration.

Note that an embodiment may also define a Unicast Get Request. Thiswould be a Get Request sent to a specific storage server. Such acapability would largely be used for diagnostic purposes, as that therewould be no end-user advantage to requesting a chunk be delivered by aspecific storage server.

A3b) Multicast Get Response

Each designated storage server will attempt to respond with a MulticastGet Response message. These responses will be collected either by theclient or by the Negotiating Group, resulting in a single source beingselected. The Multicast Get Response includes, but is not limited to,the following information:

1) The Timestamp of the response.

2) The Source ID and IP address of the responding server.

3) Identification of the Multicast Get Response that is being respondedto, and which portion of the response this is: The primary content orthe ordinal offset of which referenced chunk is being transferred.

4) The Rendezvous Group ID that will be used (which is repeated from theGet request).

5) The rate at which the chunk will be transmitted.

6) The Content Hash ID of the chunk it will deliver, and if this is anamed Chunk the Name Hash ID and unique version identifier of the chunk.

7) If the requested chunk is too large, an error will indicate thisproblem and specify the actual metadata and payload lengths. Otherwiseany immediate portion of the requested content. The entire contentsrequested consists of:

a) The Metadata Length, and the metadata and integrity checking data

b) The Payload length, length and the payload.

In some embodiments, a storage server may respond with a Content NotImmediately Available message that indicates that it cannot return thecontent requested until at least a specified time. This would typicallybe due to having previously migrated the requested chunk to offlinestorage. Issuing such a response indicates that the process of movingthe requested chunk back to online status has been initiated. However,the request should be re-issued at some time after the time indicated.

Each respondent only sends the first datagram in the response. Thisresponse is sent using unsolicited bandwidth. The balance will only betransferred once this specific server has been selected to perform therendezvous transfer using reserved bandwidth.

Unless the entire response fits in a single datagram, a single respondermust be selected to complete the transfer. This may be the Chunk Sink orthe primary member of the Negotiating Group offering to deliver thecontent. This selection is multicast as a Multicast Get Accept messageto the Negotiating Group, and the selected server will then begin thetransfer.

The selected rendezvous transfer is then initiated using reservedbandwidth by the selected storage server to the Rendezvous Groupspecified in the original Multicast Get Request.

A3c) Emergency Get Request

Before failing a request to get a chunk that is believed to existbecause there are no responses from the Negotiating Group, a requesterwill resend the Get Request to all storage nodes rather than just to theNegotiating Group.

A storage node knows that a chunk should exist when it is referenced inanother chunk, or when a request is made for an object by a client thatdoes not have a history of requesting non-existent chunks. In order toprevent a denial of service attack, repeated requests from clients forchunks that do not exist should not result in issuance of Emergency GetRequests.

A4) Volunteer Servers

Some embodiments may deploy volunteer servers to enhance the overallresponsiveness of the storage cluster. Multicast communications allowthem to be effective general purpose caching machines without forcingrequests to go through them (at the cost of slowing down all responseswhere there is no cache hit).

A4a) Accepting Content During an Initial Push

When a Volunteer Server receives a Put Proposal for content it does nothave, it may determine that it should volunteer to accept the newcontent.

The Chunk Source will understand that the response from the volunteerserver does not represent a reliably persistent storage server for thecontent. Any determination that a transaction has been successful willrequire a minimal number of designated, or permanent, members of theNegotiating Group.

The probability of a volunteer target server issuing a Put Accept for achunk should be dynamically adjusted as follows:

-   1) Having larger local storage capacity that is not currently used    should increase the probability of issuing an Additional Target    Request.-   2) Having backlogged queues of already committed work that is not    yet completed should radically decrease the probability of issuing a    Put Accept.-   3) The existence of Put Accepts from other Volunteer Servers for the    same chunk should decrease the probability of issuing further Put    Accepts.

A4b) Accepting Content Piggy-Backed on Content Delivery

When a Volunteer Server receives a Get Request for content it does nothave, it may determine that it should volunteer to hold a replica ofthis data.

The Volunteer Server issues an Additional Target Request to the samegroup that the Get Request used. The Additional Target Request requeststhat the Volunteer Server be included in the delivery as well. When anIGMP controlled multicast protocol is used the volunteer server maysimply join the Rendezvous Group specified in the Get Request. Theadditional target merely has to attempt collection of the chunk on thatmulticast group, and saving it if it is received successfully. With anon-IGMP controlled multicast protocol, the responding server will haveto add the server to the Rendezvous Group. Again, the target merely hasto attempt collection of the chunk on that multicast group, and save thechunk locally if successful. With a unicast chain put payload, the firstresponding storage server must add the server to the list, which willresult in the same chained delivery as described for the put algorithm,except that no Payload ACK message is required.

The probability of a volunteer target server issuing an AdditionalTarget Request should be dynamically adjusted as follows:

1) Having larger local storage capacity that is not currently usedshould increase the probability of issuing an Additional Target Request.

2) Having backlogged queues of already committed work that is not yetcompleted should radically decrease the probability of issuing anAdditional Target Request. The longer the delay before a delivery isinitiated (due to source/network congestion, not for delays due todelayed delivery of subsequent chunks for streaming, due to delaysshould increase the probability of issuing an Additional Target Request.A chunk which cannot be retrieved promptly will more frequently be inneed of additional replicas chunks which can be retrieved promptly. Arequest that a client had to retry is an extreme example of a longdelay, which should result in a marked increase in the probability ofissuing an Additional Target Request, perhaps even to the extent thattwo additional targets may be selected.

3) The existence of Additional Target Requests for the same chunk fromother servers should decrease the probability of issuing furtherAdditional Target Requests. Adding one extra server per chunk get isoften sufficient (this will be the subject of testing and tuningefforts).

In a preferred embodiment, Additional Target Servers should place theadditional local copies of chunks on a “short fuse” queue for deletionof these chunks with an adaptable heuristic based on Most FrequentlyUsed and Most Recently Used tagging of chunks. The chunks at the end ofthis deletion queue should be deleted from the Additional Target Serverto make room for Additional Target Requests based on the total number ofAdditional Target Requests that a Volunteer Server can support.

A4c) Responding to a Get Request for Content Held

Unlike a designated, or primary, member of a Negotiating Group, aVolunteer Server is not obligated to respond to a Get Request even ifthe Chunk is stored.

Of course, there is little point in volunteering to be an extra replica,unless the server will generally respond to Get Requests, but there areseveral reasons why it might not be advantageous to respond to aspecific request:

-   1) The work queue might already have several requests.-   2) There may be a queue to even validate whether the chunk is    locally stored.-   3) There are already responses from other storage servers that are    sufficiently equivalent (even if technically later than this server    could respond) that there is insufficient benefit in responding.

A5) Non-Immediate Requests

In accordance with an embodiment of the invention, a Get Request mayspecify non-immediate delivery. Here are some examples of whennon-immediate requests may be employed:

-   1) Retrieving archive objects from an archive with slow media (e.g.    tape);-   2) Copying an object from a server with slow media to a server with    fast media in anticipation of forecasted demand for the objects    (e.g., email boxes between 5-6 AM before start of business at 8-9    AM);-   3) Copying objects to an archive server as a replication for backup;    and-   4) Replication of chunks can be performed on a “lazy” background    basis once the minimum set of copies are guaranteed.

Non-immediate requests may be useful for applications such as retrievingarchived objects when no user is waiting for the specific content, orother cases where the consumer wishes to use low priority (andpresumably low cost) delivery resources but still eventually receive therequested chunk.

In a preferred implementation for such requests, it is best to pick themember of the Designated Group that effectively has the lowest bid forproviding the requested chunk. Rather than selecting the storage serverto perform the actual delivery based on the first responder, the membersof the Designated Group would multicast a “delivery bid” message to theother members of the group, identifying the Get Request and a nominalprice for the delivery. The lowest bidder would submit their “winning”bid to the client, and then deliver the requested chunk at that latertime.

Each storage server can apply its own heuristics to determine thenominal price to assign to its response. However, having otherdeliveries of different chunks at nearly the same time would typicallyincrease the nominal price. Factors that could lead a storage server tooffer a lower price include probable caching of the requested cachebecause of other scheduled deliveries of the same chunk, and whether thedrive storing the requested chunk would be already powered up at therequested delivery time.

Similarly, a Chunk Put Proposal can be for a non-immediate push. Therecipients of a non-immediate Chunk Put Proposal would respond witheither an indication that the chunk was already stored on this storageserver or a Put Deferred Accept message that would identify one or morebroad time windows when it could accept the chunk, and a nominal pricefor the delivery. The client would accept a window that had the lowestaggregate cost (based on the nominal prices quoted in each response) andsend a Put Deferred Accept message indicating the exact time window whendelivery will occur. The selected servers would then make the requiredbandwidth reservations. With any non-immediate delivery the target mayhave to cancel the reservation, in which case it should notify thesource so that it can seek other targets either at the same time or at alater time.

A6) Target Response

In the Chunk Put Accept response, each target indicates when it expectsit will be able to receive the bulk content of the object being put.This must be based upon both the target's internal queues for writes topersistent storage, the amount of room that will be available iningestion queues and the probable availability of network bandwidth.

Under the presently-disclosed solution, each implementation isresponsible for selected a congestion control protocol which willprevent virtually all failed message deliveries due to dropped framescaused by network congestion.

A7) Opportunistic Storage Servers

When joining an existing storage cluster, an implementation mayconfigure new storage servers to refrain from claiming the portions ofthe Hash ID ranges that a default hash algorithm would have assigned toit.

Instead, the new storage servers will retain its capacity and seek toassign itself ranges of Hash IDs when it detects the followingconditions:

-   1) When a storage server departs the ring, relatively under-assigned    storage servers will seek to claim the Hash ID range previously    handled by the now departed storage server.-   2) When get requests for a given hash id range are taking longer    than average a relatively under-assigned storage server will seek to    make itself one of the designated servers for a portion of that    Chunk Hash ID range.

B) Methods of Reliable Multicast Payload Delivery

Although multicast is typically perceived as an unreliable protocol, onmost wired LANs, the number of congestion drops or misdelivered packetsis extremely small. Since multicasts still have a non-zero probabilityof not reaching all of the target servers, Replicast has mechanisms thatadd reliability to an inherently unreliable protocol, but without theoverhead of “reliable” transport mechanisms like TCP/IP.

B1) Source Server Responsibilities

The essence of the “reliability” of the Multicast Payload Delivery isthat it does not depend on the original “source server” to insure thatall of the copies are made. The “source server” is only responsible forthe minimum set of copies. Once those copies are guaranteed, then theapplication returns control to the user application that created theobject. Replication of chunks in the presently-disclosed solution is anongoing process that does not end.

B2) Distributed, Reliable Chunk Replication

Now a distributed mechanism comes into play. Each of the Chunk copies(note that the original “source server” may be one of these chunk copiesthat is not a designated copy) keeps a list of the designateddestinations for the chunks (the size of this list is controlled by thereplication count for the object, which can also vary by object). If anyof the destinations does not yet have a copy of the chunk, then theserver holding the chunk wants to “mate” with one or more of thedestinations so as to reproduce the chunk. The distributed replicationis an ongoing responsibility of each chunk server. The replicationretries are a continuous background task for the storage servers.However, to avoid network congestion, each of the retries may be done ona random interval basis, analogous to the CSMA/CD collision detectionand retry mechanism. In this way, the replication task is spread acrossmany different servers and not left to a single source server.

This task to replicate may exist for each storage server regardless ofits retention of a list of known other replicas. Retaining such dataenables optimization of the replication process, but is not necessaryfor its correctness.

This same mechanism for performing replication may be used wheneverservers join or leave the ring of servers. Each chunk server iscontinuously updating the list of servers that have copies of a chunk(including manifests). If due to ring membership, caused by a failedserver or a partitioned network, there are insufficient replicas of achunk on designated servers, then it is the responsibility of all chunkowners to attempt to replicate to the designated servers (as noted inthe chunk manifest and hash row). Because this data can be volatile, a“get” type of query may be issued to reconstruct the list of chunkcopies.

In preferred implementations, the multicast addressing can be utilizedfor payload delivery as well as for “unsolicited commands” that carry apayload, rather than negotiating for a time to send the payload.Preferred implementations will insure that the network switch has beenprovisioned so that the bandwidth allocated for storage and“unsolicited” traffic is non-blocking up to a pre-determined limit andthat the network will not experience congestion as long as the processof reserving payload transmission does not exceed that threshold. Thishelps to ensure that the “unreliable” multicast is actually quitereliable since it does not run the risk of data loss due to networkcongestion.

While all commands and payload transfers may be retried, they can avoidthe need to retransmit by

-   -   1. Protecting the storage traffic from general purpose traffic        not complying with these special rules;    -   2. Limiting the bandwidth for unsolicited transmissions to a        provisioned rate;    -   3. Limiting the bandwidth for reserved transmissions to a        provisioned rate; and    -   4. Only utilizing the reserved bandwidth in accordance with        rendezvous agreements negotiated using unsolicited        transmissions.

C) Methods for Generating and Editing the Hash Allocation Table

The classic methods of generating a hash allocation table will typicallyresult in a fairly uniform distribution of chunks over the servers.However, it is an inflexible distribution. Existing designated hashtables may cause the cluster as a whole to be declared “full” when asingle storage server is full. The fact that there is storage availableon other servers is irrelevant; there is no space on the storage serversspecified by the distributed hash algorithm. If the chunks cannot bestored where readers will look for them, then they cannot be stored.

The improved editing of the Hash Allocation Table replaces a fixeddistribution based strictly on a hash algorithm with flexible tabledriven distribution. The table is no longer maintained by multicastdistribution of joins/departures but rather by multicast distribution ofedits.

The presently-disclosed solution relies on sharing a mapping of hash IDsto multicast addresses and/or lists of storage servers. This is referredto as a “Hash Allocation Table”. In one embodiment, the Hash AllocationTable is implemented as a memory array on each storage server withspecific methods used to guarantee that the same table is generated oneach storage server. As those skilled in the art will recognize, a“table” may be thought of as a mapping that can be implemented innumerous ways. It is defined by the data which that a key valueretrieves, rather than by the specific method used to encode and storethe rows of the table.

The presently-disclosed solution requires a Hash Allocation Table thatis updated whenever the set of storage servers changes, or whenredistribution of the workload is required. There are many methods bywhich this can be achieved:

-   1) A designated server could collect changes in the membership of    the storage cluster, generate a new hash allocation table, and then    distribute it to all servers that needed it. This technique is    compatible with the presently-disclosed solution.-   2) Having each server generate the table based on the cluster    membership reported by a distributed keep-alive ring is also    compatible with the present invention.-   3) A new method is described herein where the storage servers may    multicast edits to the entire storage cluster in a fashion where all    edits to the table will be applied, but in a consistent order by all    members of the cluster.

In accordance with an embodiment of the present invention, the HashAllocation Table may be edited on two different planes:

-   4. One plane deals with the assignment of Multicast Address Sets to    specific rows of the Hash Allocation Table. This plane also tracks    Multicast Addresses which have been provisioned for the system but    which have not been assigned to a Hash Allocation Table row.-   5. A second plane deals with the addition and deletion of storage    servers to specific rows of the Hash Allocation Table.

A versioned object created within a reserved namespace of the objectstorage system is used to assign Multicast Address Sets to rows of theHash Allocation Table and to track spare Multicast Addresses not yetassigned to a row. All servers with access to the Replicast trafficwould subscribe to this object so as to always fetch the most recentversion of this object (or alternatively to have that version pushed tothem).

The edits to the membership of the Hash Allocation Tables edit themembership status of a specific storage server for a specific row. Amembership type can be full, limited or non-existent (i.e., delete thisentry).

There are at least two valid strategies for reliably editing thememberships in the Hash Allocation Table:

-   -   There are well-known prior art techniques for the members of a        ring identified by a Keep-alive subsystem to serialize all edits        to a common table. After serialization, each member of the ring        applies the edits in order, resulting in all servers being in        agreement on what the resulting table should contain.    -   Multicasting the edits may be made reliable by having the        multicast edits be acknowledged through the keep-alive        functionality itself. After each edit, each storage server        computes the signature of the resulting table and the timestamp        of the most recent edit applied. This information may be shared        through the keep-alive heartbeat messages amongst the members of        the cluster.        -   If there is a later edit that a specific storage server had            not been aware of, it can send a multicast request that the            specific edit be retransmitted. This should result in that            server receiving the edit it had missed, applying it, and            then joining the consensus as to what the signature of the            Hash Allocation Table should be.        -   If this fails to result in consensus, ultimately the            majority of the ring will declare the minority to be wrong.            This will result in those storage servers leaving the ring,            and then rejoining it, and then having their Hash Allocation            Table be rebuilt based upon the consensus of the majority.

This technique relies upon an implicit acknowledgement of a table editin the keep-alive synchronization of the Hash Allocation Table signaturethrough the keep-alive subsystem. Inherently, the Hash Allocation Tablescannot be guaranteed to always be identical for all storage servers; thebest that can be guaranteed is that the storage servers will convergeupon having the same Hash Allocation Tables. However, thepresently-disclosed solution relies upon synchronization of the HashAllocation Table only for efficiency. Even if the complete HashAllocation Table were lost, all storage servers would seek to repair thetable claiming ranges stored locally. Once a new table was agreed upon,all servers would seek to ensure that content stored locally wasadequately retained on the designated servers, and multicast putproposals to achieve that goal. Brief discrepancies of isolated rows inthe table do not imperil the overall integrity of the distributedstorage system.

Server-Specific Heuristic Algorithms

The presently-disclosed solution describes a number of steps that mustbe implemented by specific storage servers. For example, each storageserver estimates when it will be ready to accept a chunk for permanentstorage. It is important to understand that the presently-disclosedsolution does not restrict the algorithms that any embodiment of anystorage server may use to make that estimation.

There are many methods for estimating when the work in a queue will becompleted. Many of these methods are well known. Any of these methodsare compatible with the presently-disclosed solution. The criticalrequirement is that each storage server is able to derive its ownestimate with the information provided independently without relying onany other storage server.

The presently-disclosed solution may be considered to be an enhancedversion of a “share nothing architecture” in that each storage server isindependent, and self-sufficient. Further, there are no single points ofcontention or bottlenecks in the system. However, thepresently-disclosed solution widely shares information through multicastwithin the cluster. For example, all members of the Negotiating Groupwill typically be notified of each Payload Ack for a chunk in thatgroup. This information can be used by each server's local heuristics tooptimize algorithms such as determining when a chunk should bereplicated.

The presently-disclosed solution remains a “share nothing architecture”because there is no reliance upon this shared information. It isephemeral shared status being reported through the cluster. The sharedinformation may be used to enhance behavior, but the loss of thisinformation creates no failures. Some heuristic algorithms may find lessoptimal solutions, but never an incorrect solution.

Voiding a Designated Chunk Server

A chunk server that has some functional impairment must perform twosteps without necessarily shutting down the server. First, it must leavethe ring of chunk servers as a designated destination for ingesting newchunks/objects. The byproduct of this step, as with any server thatdeparts the ring of chunk servers, is that all chunks, for which this isthe designated server, must void that server as an available designatedcopy. This in turn will trigger the step to visit each of the (nowread-only) chunks that are held on this server and begin the processes.

Variations in Participation by Negotiating Group Members

The Negotiating Group for a specific range of Chunk Hash IDs (i.e., arow of the Hash Allocation Table) identifies the set of storage serversthat should receive get or put requests for those chunks. However, notall members of this group are equal. Consider, for example, chunkservers with volatile storage and source-only chunk servers.

1) Chunk Servers with Volatile Storage:

For example, a member may indicate that it should not be counted towardthe minimum replication count. Such a server may store chunks in thisrange, and deliver them when requested. However, it might not guaranteepersistent storage. A storage server that uses only very high-speedvolatile storage (such as DRAM) is one example.

2) Source Only Chunk Servers

A storage server may also be in an impaired but still functioning state.Such a server no longer has functionality in some of the resources itrelies upon to provide persistent storage that is available on demand.

Some examples of impaired servers include:

The server may have lost one (or more) drives of a mirrored set.

The server may have lost one of several network interfaces.

While still functional, the chunks held by this storage server are now asingle hardware failure away from being unavailable. This will normallytrigger voiding the “designated” status of chunks held on this server.This should trigger process to elect a new designated storage serverthat is not in a failure state, and replicate the chunks on this serverto other servers. Impaired servers should not accept new chunks to bestored, but are still valid sources for triggered replication and forresponding to get requests.

Transaction Authentication Token

Some embodiments of the presently-disclosed solution may require theChunk Source to obtain a Transaction Authentication Token beforestarting a transaction to put the Chunks for a given object. Whenrequired, this token is obtained by supplying user credentials and theidentity of the object to be created or edited to the storage servers inthe Negotiating Group where the named chunk for the object will be putto complete the transaction.

The token will encode this information and include a signature provingthat it was signed by a storage server authorized to validate objectaccess in the object storage system. The signing storage server willhave first validated that all required access control rules for thespecific object storage system have been met.

When required by the specific implementation, this token must besupplied with each Chunk Put proposal for authentication. It may bestored as metadata to facilitate chunk cross-referencing and to enableauditing of chunk storage.

A specific embodiment may also provide a Transaction AuthenticationToken with the results for getting a Chunk that is the root of themetadata for an object. This Transaction Authentication Token would thenbe provided with each Get Request for the other chunks of that object.

Periodic Chunk Replication

Chunks are also periodically replicated to new storage servers. Thepresently-disclosed solution does not require any prioritization ofreplication. If all storage servers seek to replicate all chunks theyhave stored the storage cluster will quickly converge on having enoughreplicas of all chunks. Implementations may have specific strategies forprioritizing chunk replication so as to attempt replication on thosemost likely to need additional replicas. Reasons for optimizing specificchunks include changes in the Hash Allocation Table or for changes inimplementation specific storage policies.

The procedure to replicate a chunk is basically the same as for puttinga chunk. However, rather than supplying a Transaction AuthenticationToken a full enumeration of existing back-references for the chunk issupplied as metadata in addition to the payload.

When replicating a range of Hash IDs a storage server will replicatenamed chunks using the Name Hash ID index and use the Chunk ID index toaccess general chunks, but exclude those chunks that are used solely asNamed chunks.

Compound Get Request

In one embodiment of the present invention, the process of getting anobject is further optimized for distributed object storage systems whichstore metadata for a version of an object separately from the payload.The version manifest, or metadata, contains references to thechunks/blocks.

In a default implementation, the issuer of a Get Request may obtain theversion manifest chunk, and then issue Get Requests for the referencedpayload chunks. This pattern is used in both pNFS (parallel NFS) and theHadoop Distributed File System (HDFS).

In an optimized implementation, the storage server holding the versionmanifest chunk may originate Get Requests for a specific number of theinitial payload chunks referenced by the version manifest. Theserequests specify the originator of the Get Request as the target.

When a multicast protocol is used to deliver the payload each Chunk PutPDU specifies which chunk of the overall object it is. This informationmay be supplied in the Get Request from the storage server holding theversion manifest.

When a unicast protocol is used, the Get Request includes a port numberto be used for each of n chunks. This port number is provided in therelayed Get Request, which will identify which chunk is being deliveredto the end recipient.

Stability Across Power Reset

One desirable characteristic of a chunk distribution algorithm is thatthe same set of storage servers will reliably recreate the samedistribution after a full system wide reset. The presently-disclosedsolution retains compatibility with this feature by having each storageserver retain in persistent storage those rows in the persistent hashtable that reference them, and the total number of storage servers inthe keep-alive ring.

The keep-alive system is also required to track how long each server hasbeen a member of the ring. Upon restarting, each storage node willdetermine whether it should reapply its previous row assignments. Itwill not do so when heuristic rules suggest that it has rejoined astatic ring. Indications of this would include a large portion of themembers having been running for a configurable time period, and thepopulation of the ring being on par or greater than the previouspopulation.

Tracking Ongoing Reception

Each node in the system notes all chunk retrieval requests it receives.Even if it does not join the Rendezvous Group, it will still receiveeither a multicast Payload ACK or a Relayed ACK indicating finaldelivery status for each chunk to each member of the Rendezvous Group.While a chunk is being delivered, there is no need to start a newdelivery for the same chunk.

Extending Existing Central Metadata Systems

In an alternate embodiment, a central metadata system may be extended sothat the central metadata server specifies the location(s) of a chunk asthe Negotiating Group. The specific set of storage servers is negotiatedwithin the Negotiating Group. Chunks are retrieved by asking the centralmetadata system where they are located, and then multicasting a requestto the Negotiating Group specified for the requested chunk.

These techniques offload the central metadata server from tracking thedynamic state of each chunk/block storage server it controlled. However,these techniques would still rely on a central metadata control systemand would therefore still be constrained (throttled) in the same waythat any centralized system would be constrained.

Summary of Features and Advantages of Disclosed Object System

The presently-disclosed object system allows the set of storage serversproviding persistent storage for a chunk to be selected from those thatcan store the chunk most promptly, rather than arbitrarily selecting aset of storage servers without regard for network traffic or serverworkloads.

In prior art, selecting storage servers based upon their current loadswas limited to systems with a centralized metadata system, such as HDFSand pNFS.

The presently-disclosed object system allows the Chunk Source to selectthe optimum set of storage servers to take initial delivery of a chunkfrom amongst the Chunk Put Accept responses collected to a multicast putproposal. Centralized metadata solutions can only perform thisoptimization to the extent that the central metadata server is aware ofthe resource status of every storage server in the cluster. ExistingDistributed Hash algorithms can only adjust boundaries for longer termchanges in the distribution. Any change in the distribution of chunksrequires moving previously committed chunks. Only major changes in thedistribution can justify the migration costs of adjusting thedistribution.

The presently-disclosed object system allows the initial source of achunk to select the initial Rendezvous Group. In selecting the initialRendezvous Group, the source server has many options to influence themembers of the group. Some of the considerations include, spreadingreplicas across failure domains, selecting destinations that have thelargest amount of free space, destinations that have a best rating(combination of CPU power and memory space available) as well as otherfactors that can vary dynamically, including the speed, number and/orcost of the link(s) between the source and the sink.

The presently-disclosed object system allows storage servers with excesscapacity and currently low work queues to volunteer to provideadditional replicas of chunks. In fact, many storage systems have thenotion of “hot stand-by” drives that remain powered up, but idle, tostep in when an existing drive fails. With the presently-disclosedobject system, these hot stand-by drives can be used to perform aperformance enhancing “volunteer” duty to hold volatile extra copies ofobjects. Clients can find these additional replicas using theNegotiating Group. The Negotiating Group also enables collaborationwithin the group can be found by clients seeking those chunks and/orwhen replication of those chunks is required due to the loss of anexisting storage server (or the additional of a new storage server).

The presently-disclosed object system also allows for dynamicallyadjusting the Hash Allocation Table to dynamically load-balanceassignment of responsibilities among the storage servers. Thepresently-disclosed object system enables alternate strategies, such asholding new servers in reserve to replace failed or to offloadoverloaded servers. Prior art could only provide this type of flexibleresource assignment by centralizing the function of the metadata server.

The presently-disclosed object system also improves utilization ofnetwork bandwidth and buffering capacities.

Network elements may quote bandwidth capacities as though they werereserved. However, this is not how network elements actually operate.Buffers are not pre-enumerated for different classes of service; theycome from a common pool. Stating that the network element has a queuefor up to 40 Ethernet frames in Class X does not mean that there are 40buffers pre-allocated for that purpose. Rather, it means that after 40frames are queued for Class X, further frames for Class X may or will bedropped, and that no frames for a different Class that is below itsquota will be dropped because an excessive number of frames for Class Xwere queued.

This can be thought of as a reservoir with controlled ingress and egressrates. In aggregate, it is known that 30% of the water in the reservoircame from river W, but that does not mean that it is easy to find thespecific drops in the reservoir.

With tailored multicast as disclosed herein, the time that copies of agiven chunk will be in network element buffers is greatly reduced. Withunicast protocols, a buffer will be required for the reception time,queued time and transmit time for each of the three copies. With thepresently-disclosed solution, a single buffer will only be held for thereception time, the longest queue time of the three copies andtransmission time. While this will be more than one third of the timebuffers will be held for the unicast protocols, it is still aconsiderable improvement.

Even if there are no changes in the class of service traffic shaping forany of the Ethernet priorities, this now unused buffer capacity canenable more unsolicited messages and more non-storage packets to besuccessfully delivered over the same local area network than could havebeen delivered had a unicast delivery strategy been used. Less bufferingalso means prompt transmission, which will improve average deliverytimes.

In summary, the presently-disclosed object system provides thefollowing:

-   -   A method for distributing and retrieving chunks using multicast        addressing to Negotiating Groups and Rendezvous Groups that are        subsets of the Negotiating Groups.    -   A method for using a specialized form of Distributed Hash Table        that is a shared Hash Allocation Table to find the Negotiating        Group for a specific chunk in the absence of a central metadata        system. The Hash Allocation Table is used to locate specific        chunks the same way a Distributed Hash Table would have been        used, but the method for updating the shared Hash Allocation        Table is far more flexible.    -   A method for reliable multicast transmission of chunks that is        enabled as the result of establishing a Rendezvous Group.

Description of Drawings Illustrating Aspects of the Scalable ObjectSystem

FIG. 32 depicts a process for weighting servers in an object storagesystem in accordance with an embodiment of the invention. FIG. 32 showsthat the list of server IDs 3201 may be collected from the Ring managerthat keeps track of the current set of servers that are active. Theservers in the list are put through a process that performs a weightingprocess 3202 for the servers. In one implementation the weighing processis split into two parts 3203 for servers that handle get chunkoperations 3204 and the other for servers that handle put chunkoperations 3207. As indicated CPU and memory capacity may determineweightings for the get chunk operations 3204, while disk and memorycapacity may determine weightings for the put chunk operations 3207.

Each of these processes yields a table of hash codes (3205, 3208) thatare used by the Hash Assignment Table(s). As indicated, the getweightings may be stored in a Get Weighting Table of Hash Codes 3205,and the put weightings may be stored in a Put Weighting Table of HashCodes 3208.

FIG. 33 depicts a sample assignment of server IDs to rows of a hashtable for an object storage system in accordance with an embodiment ofthe invention. Shown in FIG. 33 is a sample (partial) list 3309 ofserver IDs. While the example storage system has more than ten storageservers, only the first ten server IDs are shown in FIG. 33 for reasonsof space.

An intermediate table 3310 with rows indicating negotiating groups towhich each server belongs is also shown. The first row (“1”) correspondsto the first server (server ID “27946418453657386492”) in the samplelist 3309 of server IDs. As shown, this first server is a member ofnegotiating groups numbers 49, 34, 21 and 10. The second row (“2”)corresponds to the second server ID (server ID “369443410833473321068”)in the sample list 3309 of server IDs. As shown, this second server is amember of negotiating groups numbers 33, 70, 9, 50, 93, 38, 85 and 34.

After all of the weighting is assigned, the hash values may be organizedinto hash rows of a hash allocation table (HAT) 3311. There are numerousalgorithms that can perform the hash organization in this fashion.Consider, for example, negotiating group 10 which corresponds to hashrow “10” in the HAT 3311. As seen in FIG. 33, hash row “10” includesserver ID “27946418453657386492” which is the first server ID in thesample list 3309 and server ID “29497889711560748519” which is theeighth server ID in the sample list 3309. Notice that both the first rowand eighth row in the intermediate table 3310 include a “10” whichindicates that the first and eighth server IDs are both members of thetenth negotiating group.

FIG. 34 depicts processing of a chunk hash ID to determine a set ofserver IDs in an object storage system in accordance with an embodimentof the invention. In FIG. 34, a chunk 3401 has its content passedthrough a cryptographic hash Algorithm 3402 (SHA256, in this example)which generates a cryptographic hash digest 3403 of the content. In theexample illustrated, that digest is further processed by a hashalgorithm 3404 which reduces the hash to a small number, assuming thatthe hash algorithm is a cryptographic hash algorithm or of similar highquality to provide for a predicatably uniform distribution of the hashresults. In the illustration the small number is represented as 00-99,but is more likely to be a power of 2 that is between 2̂5 and 2̂16. Thesmall-number hash in this example is used to index a table 3405 whichcontains the lists of servers (server IDs) that are the superset of theservers that are designated to hold the manifest for the object. In thisexample, the table 3405 would have one hundred rows due to the range ofthe hash algorithm 3404.

In an alternative implementation, each row of the table could representa range of the cryptographic hash results. Indexing the table in thisfashion would allow more precise balancing of the table at the cost ofincreasing the cost of searching it. Any implementation may considerthose tradeoffs for itself based on current processing and memorycapacities. Either method of indexing is compatible with thepresently-disclosed solution.

GLOSSARY OF TERMS

The following select definitions are presented to illuminate specificembodiments of the presently-disclosed invention, but they are notnecessarily meant to limit the scope of the invention.

Arbitrary Chunk ID—A Chunk Identifier supplied by an outside entity,such as an HDFS namenode, to identify a specific Chunk. This identityhas no known relationship with the chunk payload, but as with any ChunkID will not be re-used to reference different chunk payload for at leasttwice the lifetime of the chunk.

Better Response—A Better Response for the same chunk is “better” if thecombined Timestamp and Source fields represent an “earlier” response, orif the version of a chunk is later (more recent).

CCOW™ (Cloud Copy on Write™)—CCOW is an object storage system created byNexenta Systems that could utilize the present invention. One of thedefining characteristics of CCOW is that the chunks are:

Created once.

Accessed and replicated multiple times.

Never updated.

Eventually deleted.

Chunk—A “chunk” is typically a description for a subset of an object.That is, an object is typically split into multiple chunks. In otherobject storage systems that we have studied, the chunks of an object andthe metadata of an object are treated as two separate types of data andare treated differently and stored differently. In accordance with anembodiment of the present invention, the metadata can be accessed aseither metadata or as a chunk. Thus, the term chunk can refer to anysubset of the metadata or data for a version of an object, withoutregard to how uniform or divergent the handling of metadata is from datain a specific storage system.

Chunk ID—The identifier of a Chunk which can never refer to differentchunk payload for a period that is at least twice as long as thelifespan of a chunk. This is the Content Hash ID in an exemplaryembodiment, but it can be an Arbitrary Chunk ID supplied by acentralized metadata system (such as an HDFS namenode) in someembodiments of the present invention.

Chunk Manifest—A Chunk which holds Chunk References but which is not aVersion Manifest, but instead represents a nested portion of the fullChunk Reference list for a Version Manifest. It is referenced by itsChunk ID in the parent Version Manifest or Chunk Manifest.

Chunk Put—A Chunk Put is an operation or a PDU which transfers thepayload and metadata of a chunk to the Rendezvous Group. See ‘Chunk PutProposal’ for an explanation of how these terms may be viewed either asan operation or as a PDU.

Chunk Put Proposal—An operation, or a PDU (depending on which layer thereference is used in) which proposes a Chunk Put using reservedbandwidth. When discussing the algorithm for assigning persistentstorage responsibility, this is an abstract operation. When discussingthe specific protocol used to implement that collaboration, this is aPDU.

Content Hash ID—The Content Hash ID is a cryptographic hash (typicallySHA256 or other suitable hash) that represents a digest of the chunkpayload (after optional compression).

Designated Servers—In a preferred embodiment, the set of serversresponsible for the long-term storage of a chunk. The designated serverlist is a subset of the Negotiating Group. A server may be thedesignated server for a set of chunks.

Distributed Hash Allocation Table—A table used in the preferredembodiment implemented on multiple servers. It maps a range of Hash IDsto a Multicast Address Set and an enumerated list of designated members.When non-IGMP transport protocols are used it would also enumerate otherclasses of members.

Failure Domain—A domain where storage servers are deployed where thereis increased risk of concurrent failure of multiple servers. Therefore,it is undesirable to rely on independent replicas of a given chunk to bestored within the same failure domain. For example, two storage serversthat share a single power source would not provide two independentreplicas. A single failure could lose access to both replicas.

Gateway Servers—In a preferred embodiment, the set of serversresponsible for making special replications of chunks that do not getadded to the Chunk's replication count. These servers are used as thefront-end or gateway to either archival storage or as gateways to aremote cluster that shares knowledge of assets. The gateway server listis a subset of the Negotiating Group.

Hash Allocation Table—A collection of mappings for ranges of Hash IDs toa Negotiating Group of storage servers and a Multicast Address that canbe used to reference them. All servers in the storage cluster haveidentical Hash Allocation Tables, or at least Hash Allocation Tablesthat have no conflicting rows. The Hash Allocation Table may beconsidered to be a specialized form of a Distributed Hash Table. Chunksare found in the Hash Allocation Table in the same manner that theywould be found in a Distributed Hash Table. The Hash Allocation Table isspecialized in that it is maintained by distributed editing rather thanby being generated on each server using the Distributed Hash Table fromthe same set of inputs.

Hash ID—The Chunk Hash ID is a cryptographic hash (typically SHA256 orother suitable hash, such as SHA-512 or SHA3) that represents a digestof the chunk's data or of the Object Name Identifier (also known as theName Hash ID—typically a string of encoded text). In the presentdisclosure, this is used to control the selection of the NegotiatingGroup for a chunk, either the Name Hash ID or the Content Hash ID.

Jittered Delivery—Jittered delivery is where not all recipients willreceive their copies at the same time. Some recipients will receive achunk when it is first broadcast while other recipients will receive achunk during a later “retry” to insure that a sufficient number of thetargeted recipients have received their copies.

Keep-Alive Ring—A Keep-Alive Ring is a distributed software componentwhich enables a distributed set of servers to determine the set ofservers which have joined the ring and which are still capable ofcommunicating with the ring. Typically, when a departure or addition isdetected, each member of the ring will notify its local clients of thenew or departed servers.

Most Frequently Used (MFU)—A data item is tagged with a frequencycounter that marks how frequently it is referenced within a given timewindow. MFU may be combined with Most Recently Used to determine if adata item should be retained on a queue or deleted from a queue.

Most Recently Used (MRU)—Each time that a data item is referenced, itmay be tagged with a timestamp (many implementations are possible). Eachtime that the queue of data is referenced, the queue may be examined fora combination of MFU and MRU to determine which data items (e.g. chunks)should be removed from a queue.

Multicast Address—A Multicast Address is a network address that enablesa message to be sent to a group of destination endpoints. In mostembodiments of the present invention, this will be an IP multicastaddress.

Multicast Address Set—A set of Multicast Addresses that enables amessage to be sent to all members of a matching group. The set can berepresented as a two-dimensional array. One dimension representsdifferent parallel networks that can reach the same storage servers butover distinct network resources. For each physical network that thestorage servers are attached to, one of the multicast addresses in aMulticast Address Set is to be used. The second dimension allowsdefinition of subsets of the Negotiating Group. For example a secondmulticast address can be created for each Negotiating Group that issubscribed by servers wishing to receive notification of new namedchunks. In the preferred embodiment, the Multicast Address Set isassigned to a Distributed Hash Allocation Table using a configurationobject.

Multicast Group Address—A Multicast Group Address is a single addresswhich will direct a packet to be delivered to a group of end stations.Multicast addresses are defined for both Layer 2 and Layer 3 protocols.Ethernet is the primary example of a layer 2 protocol, while IP is theprimary example of a Layer 3 protocol.

Multicast Rendezvous Group—The Multicast Rendezvous Group is the subsetof the Negotiating Group that are selected for either getting copies ofan asset (Chunk, Chunk Manifest or Version/Named Manifest) when it isGET or PUT. In a preferred embodiment, the GET membership is the serverthat has provided delivery of the “Best Response” of the asset. The PUTmembership is the set of servers that provided not only optimum storage(e.g., quickest movement to non-volatile storage, but also the bestdiversity across “Failure Domains”).

Name Hash ID—A Name Hash ID is a Hash ID of the name of an object for achunk holding the base of the metadata for a version of an object. It isderived from the object name, rather than from the chunk content.

Negotiating Group—A Negotiating Group is the group of storage serversthat are collectively assigned responsibility to provide access toChunks for a specific range of Hash IDs. A Negotiating Group may also bereferred to as a Designated Super-Group. Typically the Negotiating Groupis found by searching the Distributed Hash Allocation Table. Each rangeof Hash IDs, which corresponds to a row in the Distributed HashAllocation Table, has a Multicast Address which can be used to addressall members of the group. Alternatively, a central metadata system (suchas an HDFS namenode) can specify the membership of a Negotiating Group.The presently-disclosed solution allows virtually unlimited scaling of astorage cluster because no matter how large a cluster is, only themembers of the Negotiating Group are relevant to the operations on anyspecific chunk. Doubling the size of the cluster only requires doublingthe number of Negotiating Groups.

Notification Servers—In a preferred embodiment, the set of servers thathave requested notification when Chunks with a matching Hash (e.g. anObject) have been updated. These servers are most office client serversor proxies that are on a notification queue that will provideinformation on updates to previously created Chunks. In the preferredembodiment, this is most frequently used for the hash of the name of anobject. The notification server list is a subset of the NegotiatingGroup.

Payload ACK—A Payload ACK is a PDU sent by the recipient of a Chunk Putmessage to indicate whether the payload was received successfully.

PDU (Protocol Data Unit)—An encoding of a message used to communicatebetween peers at the same layer, as in an OSI layered model of networkcommunications.

Persistent Storage—Storage for encoded data that is reasonably expectedto survive (be available for retrieval) even across a power outage.

Put Accept—A response to a Chunk Put Proposal that specifies whether thestorage server already has the identified chunk, or if not when it couldreceive it, or when it cannot accept the chunk at this time.

Reception Window—The time period (in microseconds) after the time of theGet Request that contains the Reception Window, when the Requestor willdesire delivery of the Get Request.

Relayed ACK—A relayed ACK is a PDU sent from the Chunk Source to theDesignated Super-Group which relays one more received Payload ACKs sothat every member of the Designated Super-Group can be aware of exactlyhow many replicas of a specific chunk have been successfully created.

Rendezvous Group—The group of storage servers selected to receive areplica of a chunk during a chosen rendezvous of chunk transmission.

Rendezvous Time Window—A Rendezvous Time Window is a proposal for, orconsensus upon, a time window for the delivery of a specific chunk to aRendezvous Group. This includes a start time, duration and a maximumbandwidth.

Rendezvous Transmission—A rendezvous transmission is a transmission ofChunk content that is multicast to a Rendezvous Group. This is a step ineither a get or a put of a chunk.

Relayed Unicast Delivery—Relayed Unicast Delivery is the simulation of amulticast delivery in a network environment where multicast is notallowed by network policies. With Relayed Unicast delivery, the packetis delivered once by the originator to the first member of theRendezvous Group using a Unicast protocol such as TCP/IP (virtualcircuits). Each recipient of the chunk with the Rendezvous Group willremove their server id from the list of recipients and then forward thechunk and recipient list to the next reachable

Service Level Agreements—Contractual arrangements between hosting orStorage as a Service (SAAS) companies and their customers that guaranteethe retention of data and the response time for the availability ofdata.

Shared and Distributed Hash Allocation Table (HAT)—A Shared andDistributed Hash Allocation Table (HAT) is an object instantiated oneach storage server, and potentially on Chunk Sources as well, whichencodes the mapping of a range of Hash IDs to Distribution Table tuples.This is most likely to take the form of a sorted array of table entries.The methods for allowing safe access to the table while allowing ongoingupdates will be implementation specific, but can include a wide varietyof techniques for doing so.

Unsolicited Commands—Commands such as get or put that have an urgent andsmall request. They will typically include the payload as part of thecommand rather than proposing that the payload is sent and waiting forround trip times to confirm the delivery request, the payload isincluded with the command. Unsolicited commands are sent usingunsolicited bandwidth. Unsolicited bandwidth is reserved stochasticallyfor an anticipated probable maximum, rather than being reserved forspecific transfers.

Version Manifest Chunk—A chunk which holds the root of metadata for anobject and which has a Name Hash ID. The term used for such chunks inthe Nexenta CCOW storage system is Version Manifest.

Volunteer Servers—In a preferred embodiment, Volunteer Servers are thoseservers that volunteer to make extra copies of a Chunk, in anticipationthat the Chunk will be requested in the near future. Analogous to theAdaptive Replacement Cache which is used in ZFS storage, in oneembodiment, the Volunteer servers use a combination of Most RecentlyUsed (MRU) and Most Frequently Used (MFU) Chunks to determine whichchunks are maintained in their local storage. The copies of Chunks thatare placed in these servers are not counted as Designated Copies. TheChunks in these servers are normally held for relatively short periodsof time and in preferred embodiments can be deleted almost at will. Theonly exception to this is, if the Chunk has not yet had a sufficientnumber of Designated copies committed to long-term storage.

III. Multicast Collaborative Erasure Encoding

The present section describes systems and methods for multicastcollaborative erasure encoding. The multicast collaborative erasureencoding taught in this section may be applied for an object storagesystem that relies upon unreliable multicast datagrams for reliabletransfer of payload within the cluster. An exemplary object storagesystem is the scalable object storage system described above in SectionsI and II.

The present disclosure provides methods and systems for multicastcollaborative erasure encoding of stored data that may be utilized withan object storage system that employs multicast replication. Themulticast collaborative erasure encoding advantageously allows forprotection against loss of individual drives or servers using lessstorage than would be required to provide the same protection with fullreplicas.

Note that the present solution is applicable to different types orerasure encoding, including XOR parity encoding using RAID Zn algorithmsand Reed-Solomon encoding. The discussion of FIGS. 37 and 38 focuses onXOR parity encoding for purposes of clarity in explanation.

Conventional Erasure Encoding

Conventional erasure encoding encodes storage assets in slices across Ndevices or servers, where the original content can be restored from alesser number M (M<N) of the data slices. For example, if M=8 and N=10(“8 of 10” encoding), then each of N=10 slices contains a different1/M=⅛ of the contents of the chunk. The N=10 slices in total storecontent the size of N/M=10/8 times the chunk size. This example of 8 of10 encoding protects against the loss of two slices.

Conventional erasure encoding reduces both network traffic and rawstorage capacity required to store an asset at the cost of greatercomputational work being required on both put and get. Without erasureencoding, a conventional object cluster can only protect against theloss of two servers by creating three replicas. This requires that thecontent be transmitted over the network three times.

With erasure encoding, a minimum of M slices, each holding at least1/Nth of the total content, must be transmitted, resulting in M/Nths ofthe payload size. This represents a considerable savings in networkbandwidth. However, this is still more than the single transmissionrequired to create N replicas as previously described for the“Replicast” transport protocol.

Conflict Between Multicast Replication and Conventional Erasure Encoding

Unfortunately, there is a conflict between the operations of multicastreplication (for example, using the above-described “Replicast”protocol) and conventional erasure encoding. While multicast replicationdelivers the same content to each storage server in a series ofmulticast datagrams sent to a negotiated Rendezvous Group in aRendezvous Transfer, conventional erasure encoding creates N differentslices of the object on N different storage servers. This conflict is aproblem that prevents conventional erasure encoding to be applieddirectly in an object storage system employing multicast replication.

Multicast Collaborative Erasure Encoding

The present disclosure provides a technique that solves this problem.The presently-disclosed technique extends the multicast replicationprotocols to allow for the reliable creation of erasure-encoded slicesof a chunk, while retaining the multicast protocol's advantageouslyefficient single transmission of a new chunk as a single completeentity. This presently-disclosed technique is referred to as multicastcollaborative erasure encoding.

Furthermore, while conventional erasure encoding requires that a singleentity perform the calculations to divide any given chunk into N slices,the presently-disclosed technique of multicast collaborative erasureencoding distributes this computational load to the receiving storageservers. This provides two advantages: first, the receiving storageservers do the calculations in parallel; and second, the calculations toerasure encode a chunk may be deferred. These advantages are highlydesirable because there are both computational and latency penaltieswhen retrieving erasure encoded content.

Note that, when assigning responsibility for holding specific stripes ofthe erasure encoding to specific servers, a preferred embodiment of thepresently-disclosed solution would not assign more than one stripe tostorage servers in a single failure domain. This is because theresources within a failure domain, by definition, have potentiallycorrelated failures. The goal of erasure encoding is to preserve thechunk if M of N stripes are retained; hence, storing multiple stripes ondevices that are prone to have correlated failures is contrary to thedata protection strategy. The assignment of no more than one stripe tostorage servers in a single failure domain is a prudent feature, but notan absolute requirement, of the presently-disclosed solution.

Regarding deferred erasure encoding, because there is a latency penaltywhen accessing erasure-encoded chunks, it can be preferable to store newcontent without erasure encoding and only perform the erasure encodingat a later time once the probable demand to access the chunk hasdiminished. In other words, it is highly desirable to first encode achunk as a full chunk at the storage servers and retain this fullencoding of the chunk while the chunk is most likely to be accessed;subsequently, when the chunk may be viewed to be in “cold storage,” thechunk may erasure-encoded into slices at the storage servers to savestorage space.

For most object cluster services, the oldest portion of the stored datais unlikely to be retrieved. For example, consider a typical e-mailinbox. The vast majority of storage is required for messages that aremore than a week old, but reading e-mail messages that are more than aweek old is very rare. So applying erasure encoding to the oldermessages is desirable, especially if new messages can remain fullyencoded for speedy retrieval.

The presently-disclosed solution has the further advantageous aspectthat the chunk does not have to be redistributed to enable erasureencoding of it. As a result, the older portion (older chunks) of thestored data may be erasure encoded in a deferred manner, while the newerportion (newer chunks) may remain full-chunk encoded. This aspectfurther saves on network bandwidth.

The presently-disclosed solution has yet a further advantageous aspectin that the re-encoding of whole chunks to erasure-encoding slicesleaves unmodified the chunk references held in the encoding of theobject metadata. This aspect is advantageous in further saving bothcomputational resources and network bandwidth.

Iterative Collaboration Using Multicast Roll Calls and Responses

The presently-disclosed solution uses multicast messaging to collect thecurrent state of how a specific chunk is stored in the object cluster.The solution then uses multicast messaging to iterate towards a desiredstate through a series of steps.

FIG. 35 is a flow chart of a method 3500 of erasure encoding of a chunkthat is stored in an object storage system with iterative collaborationusing multicast roll calls and responses in accordance with anembodiment of the invention. The method 3500 may be performed within anobject storage system with multicast replication.

i) Erasure-Encoding Roll Call

Per step 3502, an initiating node multicasts an erasure encoding “rollcall” request to the group responsible for the chunk to be erasureencoded. In the above-described object storage system with multicastreplication, the initiating node may be a storage server of the objectstorage system. The group responsible for the chunk may be thenegotiating group for the chunk, where the negotiating group isidentified using a cryptographic hash identifier of the chunk. However,alternate methods of identifying an existing multicast group for a chunkmay be used instead.

In other words, in accordance with an embodiment of the invention, whena chunk has been identified as a candidate for erasure encoding, amulticast “Erasure-encoding roll call” message may be sent to theNegotiating Group for that chunk. This message preferably includes anidentifier of the Negotiating Group, an identifier for the Chunk to beerasure encoded, the specific erasure encoding algorithm to be used, anda unique identifier of the Roll Call. One embodiment of the Roll Callidentifier is formed by concatenating a timestamp and the IP address ofthe requester. Alternately, the Roll Call identifier may be aconcatenation of a sequence number and the source IP address.

ii) Roll Call Inventory Response

Per step 3504, each node in the group receiving the request multicasts a“roll call inventory” response to the “roll call” request to all theother nodes in the group. The roll call inventory response messageidentifies: a) the roll call message being responded to; b) the specificstorage node that is responding; c) whether this storage node has storedin it a whole replica of the specified chunk; and d) which, if any,erasure encoded slices this storage node has (or has begun building) forthis specified chunk. In other words, each roll call inventory responsefrom a node enumerates the encodings of the chunk (whole and/or specificerasure encoded slices) that are stored at that node.

In other words, in accordance with an embodiment of the invention, eachrecipient of the erasure-encoding roll call request responds with anerasure-encoding chunk inventory multicast message which it sends to thesame Negotiating Group. This roll call inventory response may preferablyinclude:

the echoed identifier of the roll call request;

the identity of the responding object storage server instance;

the identifier of the chunk being queried; and

how the identified chunk is encoded on local storage by this instance.

In an exemplary implementation, “how the chunk is encoded on localstorage” may be: not at all; a whole copy; or slice number n of Naccording to the specified erasure-encoding algorithm, which divides thechunk into a total of N slices.

In exemplary implementation, in addition to a roll call inventoryresponse, a node of the group may further respond to a roll call requestby multicasting an offer to voluntarily compute a slice forCPU-challenged storage nodes. Such an offer may include whether thewhole chunk was already stored on the offering node, and a commitment asto how quickly a requested slice could be computed. In this case, a nodethat has assigned itself the responsibility to compute a slice may electto contact the volunteering server if it is committing to provide a copyearlier than the storage server could compute the answer itself. Such adecision may consider recent levels of network congestion; the fact thatanother node can compute a slice more quickly is irrelevant if thenetwork transfer cannot be completed promptly.

iii) Collection of Roll Call Inventory Responses

Per step 3506, every node in the group collects “roll call inventory”responses that respond to the “roll call” request. By having every nodein the group collect the roll call inventories, every node has theinformation needed to evaluate the collective inventories within thegroup to formulate a same set of actions. While every member of thegroup collects the full set of inventory responses that it receives forany given roll call request, a dropped message may be simply ignoredwithout a retransmission request.

Note that a storage server may receive Roll Call Inventory responses toa Roll Call request that it did not hear. Embodiments are free to eitherignore such messages, or to retroactively infer reception of the RollCall request by not only collecting the response but responding to it aswell.

iv) Evaluation of Roll Call Inventory Responses and Determination ofSubset of Actions to be Performed by Individual Node

Per step 3508, every node in the group evaluates, in parallel, thecollected roll call inventory messages to determine the set of actionsthat are required. The logical evaluation by a node may begin once rollcall inventory response messages have been received from all members ofthe group, or after a predetermined time has elapsed that is sufficientsuch that no more responses can be reasonably expected. In an exemplaryimplementation, the set of actions determined may include: multicastingthe whole chunk to create new replicas at other nodes in the groupand/or encoding (and potentially transferring) slices of the chunk. Theevaluation depends upon the collective roll call inventories from thenodes in the group. The evaluation depends on which nodes in the groupalready stores a whole replica of the chunk and what slices alreadyexist, or are already being constructed, at the nodes in the group.

In other words, each member of the group evaluates the collectedresponses, determines the collective action required (if any), andassigns itself a portion (if any) of that work. This assignment is basedupon parallel evaluation that orders both the tasks to be done and theavailable storage nodes. Any ordering algorithm is acceptable as long asall members of the nodes will assign the same work to the same storagenodes without the need for active collaboration.

Per step 3509, every node in the group determines a subset of the set ofactions to be performed by itself. The subset of actions assigned to anode is determined in a same agreed-upon manner at each node in thegroup. The subset of actions for a particular node may depend upon theparticular node's place in the ordering of the nodes in the group. Theordering may be, for example, a sorted order based on a node identifier.

In an exemplary implementation, the analysis of the collected roll callinventory responses and the determination of the subset of actions to beperformed by a node are described further below under the section“Analysis of Collected Inventory Responses.”

v) Performance of Subsets of Actions by Nodes in the Group

Per steps 3510-n, for n=1 to Ng, where Ng is the number of nodes in thegroup, the nth node in the group performs an nth subset of actions. Thesubset of actions to be performed by a node being determined in step3509 as discussed above. As mentioned above, the actions may includemulticasting the whole chunk to create new replicas at other nodes inthe group and/or encoding (and potentially transferring) slices of thechunk. (Note that it is possible that a subset of actions may be empty,in which case the node corresponding to that subset is not assigned toperform any action.)

vi) Selection of Pseudo-Random Times for New Roll Call Request

Per steps 3512-n, for n=1 to Ng, when a node completes its assignedsubset of actions, a time may be selected for a new roll call request.The time may be selected pseudo-randomly to distributed the selectedtimes amongst the nodes in the group. At the selected time, the new rollcall request may be multicast from the node to the group. However, if anerasure-encoding roll call for the same chunk is received before theselected time, then the multicasting of the new roll call request at theselected time will be pre-empted for the node.

In other words, after completing its work pursuant to a priorErasure-encoding roll call, a storage node will pseudo-randomly select atime to issue a new Erasure-encoding roll call for the chunk. The newErasure-encoding roll call for the chunk will be pre-empted should anErasure-encoding roll call for the same chunk be received before thenode's own new Erasure-encoding roll call is issued.

The above-described pseudo-random mechanism that distributes theissuance of new roll call requests advantageously prevents multiplenodes from flooding the available network at the same time.

vii) Next Iteration Initiated by New Roll Call Request

Upon a new roll call request being sent by any one of the nodes, thenthe method 3500 loops back to step 3514 and a next iteration isperformed. In this way, the method collaboratively iterates in a dynamicmanner to a desirable state. In accordance with an embodiment of theinvention, the procedures of the presently-disclosed solution convergeupon a stable encoding of the chunk, either as whole replicas, or aserasure-encoded slices. Lost replicas or lost slices may be replacedthrough background scanning of the multicast group.

Note that the method 3500 depicted in FIG. 35 uses a pseudo-randommechanism to select in an ad-hoc manner the executor of the next rollcall. An alternate embodiment may utilize a deterministic way of,effectively, determining the master of the next iteration. For example,one deterministic technique would be to issue the next roll call fromthe first node ID in a sorted list of node IDs of the nodes that takepart in the iteration. Other pseudo-random or deterministic techniquesmay be used in other implementations.

Comparison with Unnamed Chunk Get Sequence with Cluster Consensus

Note that, the sequence of the erasure-encoding roll call and theerasure-encoding chunk inventory messages has some similarities with theUnnamed Chunk Get Sequence with Cluster Consensus in the above-describedreplicast protocol. However, there are the following differences.

First, the goal is to determine what actions are required, rather thanto get an existing replica. An Erasure Encoding Roll Call may lead tocreation of new erasure-encoded slices and making whole replicasremovable. However, this is a goal achieve over an iterativecollaboration. The process by which a Unnamed Chunk Get results in aRendezvous Transfer in the base Replicast protocol is far more direct.

Second, the storage nodes therefore have less discretion to simplyignore the unsolicited message when they are backed up (as they can withUnsolicited Gets), and therefore more tolerance must be granted fortime-delay Inventory responses.

Analysis of Collected Inventory Responses

According to one embodiment of the invention, in logically analyzing thefull set of inventory responses, each storage server may diagnose one ofthe following conditions.

a) There are insufficient replicas (whole or erasure encoded slices) ofthis chunk. Replication procedures as defined for the Object cluster areto be applied to create more whole replicas (for example, if the storagegoal is to store multiple whole replicas of the chunk) or create furthererasure-encoded slices (for example, if the storage goal is to storeerasure-encoded slices).

b) There are sufficient whole replicas, but the replication count R forslices is less than a target number of N erasure-encoded slices. In thiscase, the selection algorithm may assign responsibility to generatemultiple slices to the servers already holding the chunk, and thenhaving those servers replicate the extra slices to their selected homes(i.e. to the storage servers of the negotiating group selected to holdthose slices). In this way, the replication count R for slices may beraised to the target number of N.

c) There are missing slices for this chunk such that the replicationcount R for slices is less than the number M needed to reconstruct awhole chunk, and this storage server has a whole replica of the chunk.In this case, this storage server may generate an enumerated (ordered)list of the responding servers. The enumeration may first list (at lowerordinal numbers) only those servers that currently have the whole chunkstored, and then enumerate (at higher ordinal numbers) the servers thatdo not currently have the whole chunk but may obtain it. The orderingmay also factor in the available capacity and latency of the storageservers. Sorting within each category (whole chunk stored, or do notcurrently have the chunk) may be based upon the network addresses of thestorage servers, for example. Other enumerations and sortings may beused, so long as the same algorithm is applied for all members of thegroup.

If the storage server is at ordinal number n in the enumerated list,then it may assign to itself the action or task of creating the nthslice of the chunk (the slice being generated as a derivative of thewhole chunk). Furthermore, if there are also insufficient copies of thewhole replica of the chunk, then the first member of the group that doesnot have a whole replica may initiate a replication of the whole chunkto the negotiating group.

d) All slices of the chunk are represented in the collected responses.When this condition occurs, the original data holding the whole chunkencoding may be deleted by this storage instance.

e) There are insufficient slices and no whole representationrepresented. In this case, the best member of the cluster (the one thatcan perform the task quickest) should initiate a Get of the chunk,resulting in it storing the entire chunk.

According to another embodiment of the invention, the state diagram ofFIG. 36 may be utilized in the analysis of the collected roll callinventory responses and the determination of the subset of actions to beperformed by a node. The state diagram illustrates the life cycle of asingle chunk as it may be encoded as replicas and/or slices inaccordance with an embodiment of the present invention. The statediagram further shows how loss of stored replicas or slices are dealtwith.

As depicted, the state may depend on the goal for the storage of thechunk. In an exemplary implementation, a first storage goal 3601 may bestoring multiple whole replicas of the chunk, and a second storage goal3611 may be storing erasure-encoded slices of the chunk. As describedabove, for example, the first goal 3601 may be applied to frequentlyaccessed chunks, while the second goal 3611 may be applied rarelyaccessed chunks.

For a chunk that has the first storage goal 3601, there may be twodifferent states, where the state is determined based on the roll callinventory responses.

A first state 3602 under the first storage goal 3601 may be a stablestate where it is determined that there are sufficient whole replicasencoded and distributed within the group such that the chance of losingall replicas is acceptably remote.

A second state 3604 under the first storage goal 3601 may be a statewhere it is determined that there are insufficient whole replicasencoded and distributed within the group. In this case, the chance oflosing all replicas (i.e. going to state 3622) is unacceptably high. Assuch, a replication procedure as defined for the object cluster may beapplied to increase the number of whole replicas.

In the replication procedure, one of the nodes with a whole replica mayelect itself to replicate the chunk to more nodes of the group. In anexemplary implementation, every member of the group elects itself with apseudo-random delay. Hence, all but one member will see anotherreplication already initiated, and hence cancel its own replicationattempt before it is launched.

For a chunk that has the second storage goal 3611, there may be fourdifferent states, where the state is again determined based on the rollcall inventory responses.

A first state 3612 under the second storage goal 3611 has insufficienterasure-encoded slices, but it has whole replicas still available withinthe group. Because there are insufficient slices, the whole replicas arenot yet eligible for deletion. For example, this state 3612 may beentered when the storage goal changes from the first goal 3601 to thesecond goal 3611.

In this state 3612, in an exemplary implementation, the actiondetermination algorithm may assign responsibility to generate multipleslices to servers already holding the whole chunk and/or to servers notyet holding the whole chunk. In the latter case, the whole chunk may befirst replicated to the servers. The responsible servers may generatefurther slices (which are basically blobs derived from the whole chunk)and then replicate the further slices to their selected nodes.

Thereafter, roll call requests may continue to be issued (afterpseudo-random delays) as discussed above in relation to FIG. 35, and theslice building may thus continue until sufficient slices are availablein the group. Once sufficient slices are available in the group, thestate may change to the second state 3614.

A second state 3614 under the second storage goal 3611 has sufficienterasure-encoded slices. This state also has whole replicas stillavailable within the group, but these whole replicas are now eligiblefor deletion. When there are no whole replicas left, the state for chunkencoding transitions to the third state 3616 under the second storagegoal 3611.

In this third state 3616, there are sufficient erasure-encoded slicesand no available whole replicas. If slices are lost such as the slicesare no longer sufficient, then the state for chunk encoding maytransition to a fourth state 3618 under the second storage goal 3611.

This fourth state 3618 may be a state where it is determined that thereare insufficient erasure-encoded slices and no whole replicas remainingin the group. In this case, the chance of losing too many slices (i.e.going to state 3624) is unacceptably high. As such, a slice rebuildprocedure is put in process. Once sufficient slices are available in thegroup, the state may change back to the third state 3616.

Tolerance for Lost Roll Call Inventory Responses

In an exemplary implementation, the multicast communications used forErasure Encoding Roll Call messages and Inventory responses is madeeffectively reliable through the use of a congestion control algorithmsuch as above in relation to multicast replication (replicast).

However, it may be noted that there is no permanent harm should anincomplete set of Roll Call Inventory messages. The worst that canhappen is that work assignments include creation of slices that wereactually already stored in the cluster or that multiple storage nodeswill assign themselves the same work. While these mistaken steps areregrettable, they will not harm the object cluster.

Whole replicas are only eligible for deletion when the collected set ofInventory responses shows a complete set of slices to be availableand/or excessive whole replicas are available. The absence of datacannot enable deletion of content that would not have been deletedanyway.

Embodiments of the present invention therefore merely have to ensurethat dropped messages are rare. The present invention is tolerant ofindividual drops of Roll Call Inventory messages.

Stateless Get Extended for Erasure Encoding

To be compatible with erasure encoding, the replicast protocol forresponding to an Object Get request may be extended such that, inresponding to an Object Get request, a storage instance may indicatethat it only has slice n of N with erasure encoding algorithm X forChunk Y. In other words, the processing of a multicast Get Request isextended to allow a Get Response to additionally report that a specificslice of a chunk is available from this source, rather than the wholechunk. This response would still indicate when the data being offeredcould be made available.

The Get Responses must be evaluated to determine from which sources toschedule Rendezvous Transfers. The above-described multicast replication(replicast) protocol already describes processes (client consensus andcluster consensus) for selecting the “best” response to an Object Getrequest. The process for reaching a consensus may be extended by addingthe following rules or preferences.

Get responses with whole encodings of the whole chunk are generallypreferred over Get responses with slices of the chunk. However, ifslices can be fetched iteratively and a whole replica reconstructedbefore an existing whole chunk would be available, then the Get Acceptmessage may specify a rendezvous transfer with the server thatreconstructs the whole replica. The most common case here will be whenthere is no whole copy of the Chunk available nearby in the ObjectCluster, but it is possible that a whole chunk could be available froman archive service or a remote segment of the Object Cluster. In thiscase, it may be predictably faster to rebuild from local slices ratherthan to start a remote fetch of the whole object.

If slices are used, they are preferably retrieved from the specificservers holding them. Missing slices may be regenerated according to thetechnique discussed in the “Distributed Slice Regeneration” section. Thereassembly process may be then applied by the server that issued theObject Get request. The chunk reassembled from erasure-encoded slices isthen subject to normal chunk validation procedures, including validatingthat its content still matches its cryptographic hash.

Keeping track of the chunks that are subject to erasure encoding (andthe chunks that are not) may be done in metadata.

Note that when a storage instance leaves the Negotiating Group, a RollCall request should be issued for each Chunk that the departed instancepotentially stored. This would be a normal part of the replicationprocess triggered whenever a storage instance departs.

Deferred Erasure Encoding

The presently-disclosed solution does not require a chunk to be erasureencoded when it is initially put to the object storage cluster.

Any retrieval of a chunk that has been erasure encoded will requirewaiting on more storage nodes and require the extra step of assemblingthe content. Because of these unavoidable penalties, it will befrequently advantageous to initially store a chunk with whole replicasand defer the storage space savings of erasure encoding until a latertime when the retrieval demand for the specific chunk has diminished.Storage systems typically see a rapid drop in the probability that agiven chunk will be accessed as the chunk ages. For example, a chunkholding portions of today's email will have a higher probability ofbeing read than a chunk holding month-old email.

The presently-disclosed solution includes a transition from encoding achunk as whole replicas, to creating slices in addition to the wholereplicas and then allowing for eventual deletion of the whole replicas.

Distributed Slice Regeneration (Distributed Recovery of Lost Stripe)

FIG. 37 depicts a conventional method of recovery of a lost stripe froma parity stripe. As shown on the left of the diagram, the chunk may bestored in multiple stripes: S1; S2; S3; and S4, where in this examplefour stripes are used. Other numbers of stripes may be used in apractical implementation. In addition, a parity stripe S1̂S2̂S3̂S4 isstored, where the A symbol represents a bit-wise XOR operation. Notethat the terms “slice” and “stripe” are used in a largelyinterchangeable manner in the present disclosure.

If, for example, the S4 stripe is lost or otherwise not obtainable, thenthe chunk may still be recovered using the parity stripe. The operationto recover the S4 stripe is represented by: S1̂S2̂S3̂(S1̂S2̂S3̂S4)=S4.

FIG. 38 depicts a method of distributed recovery of a lost stripe from aparity stripe in accordance with an embodiment of the invention. Asshown on the left of the diagram, the chunk may be stored in multiplestripes: S1; S2; S3; and S4, where in this example four stripes areused. Other numbers of stripes may be used in a practicalimplementation. In addition, a parity stripe S1̂S2̂S3̂S4 is stored,where the A symbol represents a bit-wise XOR operation.

If, for example, the S4 stripe is lost or otherwise not obtainable, thenthe chunk may still be recovered using the parity stripe. However, theoperation to recover the chunk is different from the conventional methodof recovery.

As shown in the diagram, the recovery calculations are broken down intoportions that require different subsets of the entire chunk to beassembled. In the example depicted, a first portion of the recoverycalculation is performed at a first node that performs the operationS1̂S2=(S1̂S2), and a second portion of the recovery calculation isperformed at a second node that performs the operationS3̂(S1̂S2̂S3̂S4)=(S1̂S2̂S4). A third portion of the recovery calculationmay then be performed from the results of the first two portions by theoperation (S1̂S2)̂(S1̂S2̂S4)=S4. The third portion may be performed at athird node (or at one of the first two nodes).

Advantageously, the end result is that the rebuild of the slice may becompleted in less time. This is because more nodes and network links maybe utilized in parallel.

Further description of details relating to distributed sliceregeneration is as follows.

Note that when the erasure-encoding algorithm has the characteristicsthat the decoding steps may be performed in varying order, the presentsolution can optimize the processing of rebuilding a lost stripe of achunk.

Note also that RAID protection of objects may be implemented using thepresent solution of erasure encoding. For example, replication with twoadditional whole copies may be described as erasure encoding with M=1 (asingle slice needed to reconstruct the whole chunk; i.e. the slice isthe whole chunk) and N=3 (three replicas stored), giving an encodingrate of M/N=⅓.

As an example of RAID protection, RAID 5 (distributed parity) may bedescribed as erasure encoding with, for instance, M=4 (four slicesneeded to reconstruct the whole chunk) and N=5 (five slices stored),giving an encoding rate of M/N=⅘. More generally, M=N−1 for RAID 5.

As an example of RAID protection, RAID 6 (distributed parity with twoparity blocks) may be described as erasure encoding with, for instance,M=4 (four slices needed to reconstruct the whole chunk) and N=6 (sixslices stored), giving an encoding rate of M/N=4/6. More generally,M=N−2 for RAID 6.

Consider an exemplary implementation where the data is striped over Ndata stripes, with 1, 2 or 3 parity stripes. The first parity stripe isreferred to as P. It is a simple parity of the data stripes. Theoptional 2^(nd) (Q) and 3^(rd) (R) stripes are also calculated from thedata stripe, but use a more complex algorithm.

When a single data stripe has been lost, it can be rebuilt by XORing thesurviving data stripes with the P stripe. For example, if there are 7data stripes, and stripe 6 has been lost, then each byte in stripe 6 canbe rebuilt with the formula:

S6=S1̂S2̂S3̂S4̂S5̂S7̂P

Because P is S1̂S2̂S3̂S4̂S5̂S6̂S7 the result XORing with the survivingdata slices is S6.

In a conventional implementation, the rebuilder fetches all sixsurviving data stripes and the Parity stripe to rebuild. However, in anetworked rebuild, this requires a single storage node to receive all ofthe surviving stripes and the parity stripe. Effectively the size of theentire chunk must be received to re-create a single lost stripe.

Because lost stripes are relatively rare, a larger concern is for thelatency in rebuilding a lost stripe, rather than for the total volume ofnetwork traffic. Because the typical chunk is retrieved many times foreach time it must be rebuilt, the impact of rebuild traffic on overallnetwork load will be light. However, reducing the rebuild time makes thestorage cluster more robust. The purpose of protecting against the lossof multiple slices is to protect against the loss of one or moreadditional slices before the lost slices are reconstructed. The risk oflosing a chunk is therefore directly proportionate to the time it takesto restore a single lost slice.

The present solution shortens the time required to reconstruct a singlelost slice by performing the XOR operations in parallel, as follows:

-   -   The set of surviving slices and P are paired. One member of each        pair sends its stripe to the other. The receiving member XORs        its stripe with the received stripe. If there is an odd number,        the “odd man out” conceptually sends to itself and XORs with all        zeroes (i.e. it just declares itself to be ready for the next        round, no real work is required).    -   This continues with the set of nodes that received a stripe,        they are paired and one sends its accumulated XORred stripe to        its partner.    -   Eventually this results in a single copy which has XORred the        entire set, and re-created the lost slice.

For Example:

-   -   The surviving slices are S1,S2,S3,S4,S5,S7. Slice S6 will be        recovered using the P Slices which was created with the content        S1̂S2̂S3̂S4̂S5̂S6̂S7.    -   Step one in parallel do:        -   S1⊕S2    -   (S2 is sent to holder of S1, which XORs them together),        -   S3⊕S4        -   S5⊕S7    -   And do nothing immediate with Slice P (odd man out).    -   Step two, in parallel do:        -   (S1⊕S2)⊕(S3⊕S4)        -   (S5⊕S7)⊕P    -   Step 3:        -   ((S1⊕S2)⊕(S3⊕S4))⊕((S5⊕S7)⊕P)

Which yields S6.

Because all three operations in the first phase are performed inparallel, as are the two operations in the second phase, the pipelinedelay is the transmission time of 3 slices. This compares favorably to adelay of 7 slice-transmission-times for the non-distributed rebuild (or4 vs 8 if a final copy of the restored S6 is included). This assumesthat the storage nodes have symmetric transmit and receive capabilities,and therefore a single node cannot receive two stripes “at the sametime” without slowing transmission of each of them down. This recoveryprocess can also be accomplished by any reversible algorithm that can bedecomposed into steps which can be performed in parallel on looselycoupled processors.

Given the pairing-off process for distributed regeneration of a slice,the optimal erasure encoding for a slice would have the number of slices(N) be a power of 2.

Distributed Chunk Verification

Each slice of a chunk is protected by some form of error detectionseparate from the cryptographic hash verification available for theentire chunk.

One method of doing so is to simply apply the same cryptographic hashalgorithm to each slice of the chunk. While convenient, this is actuallycomputational overkill. The only requirement for slice error detectionis error detection. There is no need for distributed de-duplication orprevention of spoofed content for slices, only for whole chunks.

Individual storage nodes can perform periodic scrubs on stored slicesusing the slice error detection field. In addition, background objectreplication tasks can validate that there are sufficient slices of achunk still intact on a sufficient number of storage nodes. However, toprotect against storage nodes mistakenly storing the wrong data for aslice of a chunk, it is desirable to periodically validate thatcryptographic hash of the entire chunk.

The present solution does so without requiring the whole chunk to beassembled as follows:

-   -   The data is sliced so that the first 1/Nth of the chunk is        placed in the first slice, then next 1/Nth in the second slice,        etc. Traditional RAID algorithms rotate the encoding of slices        assuming that the size of the data is variable and to evenly        spread retrieval work across the slices. Those factors are not        relevant for a chunk, which is always retrieved as a whole    -   The storage node holding the first slice begins a cryptographic        hash calculation of the data held in the first slice. When the        storage node completes passing over the data it holds, it        snapshots the cryptographic hash calculation, and sends a        serialization of the cryptographic hash calculation to the        storage node holding the second slice of the chunk. The snapshot        is the state of the cryptographic hash computation which        includes the state of intermediate hidden variables in the        cryptographic hash engine, which are preserved and transmitted.    -   The storage node holding the second slice re-initializes the        cryptographic hash engine with the serialized snapshot, then        applies the cryptographic hash algorithm to its payload. It then        snapshots the state of the cryptographic hash engine so that it        can be forwarded to the storage node holding the next slice of        the object.    -   This continues until the storage node holding the final slice of        the chunk has the cryptographic hash of the entire chunk, which        can be compared to the original cryptographic hash of the entire        chunk. Any change indicates corrupted data.

An alternative technique can provide for more rapid verification of thecryptographic hash of a sliced chunk, but does require more localstorage. With this method:

-   -   Each storage node holding a slice of the chunk retains the        cryptographic hash snapshot received from the prior slice and        the resulting cryptographic hash is sent to the following slice.    -   Each storage node can validate on its own that applying the        payload held for its slice of the chunk starting with the prior        cryptographic hash snapshot will result in the same post        cryptographic hash snapshot as recorded. If the result is not        the same, then the stored slice has been damaged.    -   If these snapshots are included in the Roll Call Inventory, or        in a similar transaction, the storage nodes can validate that        their post snapshot matches what the next slice has its        pre-snapshot. If there are mismatches, it indicates that the        chunk has been corrupted. The storage node with inconsistent        data must be identified, and its copy declared to be invalid, so        that regeneration of the slice can proceed.

Summary of Benefits

The presently-disclosed solution has several advantages compared toconventional Object Clusters or conventional Erasure-Encoding ObjectClusters. The presently-disclosed solution adds the benefits of erasureencoding for improving utilization of raw storage capacity whilepreserving the optimizations that the Replicast protocol obtains fromthe use of multicast messaging.

Specific advantages include:

-   -   The gateway node that ingests the chunk does not have to perform        the erasure encoding algorithm, potentially eliminating a CPU        bottleneck.    -   Network transfers of content are minimized when converting an        object from whole replica protection to erasure encoding        protection.    -   Erasure encoding can be deferred until desirable, radically        reducing the overhead of accepting new content.    -   No metadata modifications are required when changing chunks from        being replica protected to erasure encoded. Metadata references        to the chunk are indifferent to how the chunk is stored.

Conventional erasure encoding with a conventional object cluster placesa transactional cost on the use of erasure encoding while reducing theraw amount of storage required to achieve the same protection from lostdevices. However, multicast-enabled erase-encoding is better than aconventional object cluster or conventional erasure encoding with aconventional object cluster. Specifically:

-   -   For Put transactions        -   Network bandwidth for put transactions may be optimized. In            contrast, to protect against the loss of two replicas, a            conventional object cluster will fully transmit the object            payload on each of three distinct connections. The latency            of the transaction will be the worst of the three            consistent-hash selected servers.        -   Conventional erasure encoding will transmit slightly more            than 1/Mth of the payload on up to N different connections            to achieve M of N protection. Even with 2 of 4 encoding,            this is still a major reduction in network bandwidth. The            latency of the transaction will be the worst of the M            selected servers, which may be less than a conventional            object cluster for larger chunks, but inferior when the            variance in server latency is high relative to the latency            of putting a chunk.        -   Replicast-enabled object clusters only have to transmit the            chunk payload once to create R replicas. The latency of            completing the write transactions is optimized compared to            consistent hashing solutions because the servers are            typically selected based on their immediate availability.            That is, for example, the 3 most available servers in the            negotiating group will typically be selected to store the            new chunk.        -   The present solution typically defers erasure encoding of            chunks, but even if performed immediately, the chunk payload            is transmitted just as with the above-described “baseline”            replicast-enabled object cluster; effectively transmit once,            receive many, and erasure encode eventually.    -   For Get transactions:        -   A conventional object cluster picks one of the replicas with            which to perform an initial get transaction. When there is            no error, the speed is determined by the average latency of            a storage server within the cluster.        -   A conventional erasure-encoding object cluster must complete            the get of at least M of N slices. Because all slices must            be received at a single chokepoint, and the total amount of            data to be received is increased, this will typically take            longer than with a conventional object cluster.        -   A Replicast object cluster without erasure-encoding must            wait for the best replica's response time.        -   An erasure-encoded object within a Replicast object cluster            will have to wait for the worst time of the N selected            servers, but the M minus N servers with the worst projected            fetch times can be ignored, allowing a slight improvement            over conventional erasure encoding solutions.

CONCLUSION

In the above description, numerous specific details are given to providea thorough understanding of embodiments of the invention. However, theabove description of illustrated embodiments of the invention is notintended to be exhaustive or to limit the invention to the precise formsdisclosed. One skilled in the relevant art will recognize that theinvention can be practiced without one or more of the specific details,or with other methods, components, etc.

In other instances, well-known structures or operations are not shown ordescribed in detail to avoid obscuring aspects of the invention. Whilespecific embodiments of, and examples for, the invention are describedherein for illustrative purposes, various equivalent modifications arepossible within the scope of the invention, as those skilled in therelevant art will recognize. These modifications may be made to theinvention in light of the above detailed description.

What is claimed is:
 1. A method of multicast collaborative erasure encoding of a chunk stored in a distributed object storage cluster, the method comprising: multicasting a roll-call request to every storage server in a negotiating group for the chunk; generating and multicasting roll-call inventory responses by every storage server in the negotiating group; and collecting the roll-call inventory responses by every storage server in the negotiating group from other storage servers in the negotiating group to form a set of roll-call inventory responses.
 2. The method of claim 1, wherein the roll-call request comprises: an identifier for the negotiating group; an identifier for the chunk; and an identifier for the roll-call request.
 3. The method of claim 2, wherein the roll-call request further comprises: identification of a specific erasure-encoding algorithm to be used.
 4. The method of claim 2, wherein a roll-call inventory response multicast by a storage server comprises: the identifier for the roll-call request; an identifier for the storage server; whether a whole replica of the chunk is stored at the storage server; and which, if any, erasure-encoded slices of the chunk are stored at the storage server.
 5. The method of claim 1, wherein a roll-call inventory response that is missing due to not being collected by a storage server is ignored without a retransmission request.
 6. The method of claim 1, further comprising: performing a logical evaluation of the set of roll-call inventory responses by every storage server in the negotiating group.
 7. The method of claim 6, wherein the logical evaluation by a storage server begins after the roll-call inventory responses have been received from every storage server in the negotiating group or a predetermined time has elapsed.
 8. The method of claim 6, wherein the logical evaluation diagnoses a state with a whole replica of the chunk held by at least one storage server and a replication count for erasure-encoded slices that is less than a target number of erasure-encoded slices, the method further comprising: assigning actions to the storage servers holding a whole replica of the chunk to generate erasure-encoded slices and replicate the erasure-encoded slices to storage servers in the negotiating group that are selected to hold the slices.
 9. The method of claim 6, further comprising: each storage server in the negotiating group determining a subset of actions to be performed by itself based on the set of roll-call inventory responses; and each storage server in the negotiating group performing the subset of actions to be performed by itself.
 10. The method of claim 9, further comprising: selection of a storage server in the negotiating group to multicast a new roll-call request for the chunk.
 11. The method of claim 10, wherein the selection of the storage server in the negotiating group to multicast the new roll-call request comprises: each storage server in the negotiating group pseudo-randomly selecting a time to multicast a new roll-call request for the chunk, wherein the new roll-call request is not issued if pre-empted by receipt of the new roll-call request as multicast by another storage server.
 12. A distributed object storage system that stores objects in chunks, the system comprising: a plurality of storage servers communicatively interconnected by a network; and negotiating groups for the chunks, wherein a negotiating group for a chunk comprises a group of the storage servers that are assigned to store and provide access to the chunk, and wherein a storage server in the negotiating group for the chunk includes executable code that performs steps including: multicasting a roll-call request to other storage servers in the negotiating group for the chunk; collecting roll-call inventory responses received from the other storage servers in the negotiating group for the chunk to form a set of roll-call inventory responses; and performing a logical evaluation of the set of roll-call inventory responses.
 13. The system of claim 12, wherein the executable code performs further steps including: receiving the roll-call request from another storage server in the negotiating group; and multicasting a roll-call inventory response to the negotiating group in response to the roll-call request.
 14. The system of claim 13, wherein the roll-call request comprises: an identifier for the negotiating group; an identifier for the chunk; an identifier for the roll-call request; and identification of a specific erasure-encoding algorithm to be used.
 15. The system of claim 13, wherein the roll-call inventory response comprises: the identifier for the roll-call request; an identifier for the storage server; whether a whole replica of the chunk is stored at the storage server; and which, if any, erasure-encoded slices of the chunk are stored at the storage server.
 16. The system of claim 12, wherein the logical evaluation by the storage server begins after the roll-call inventory responses have been collected from every storage server in the negotiating group or a predetermined time has elapsed.
 17. The system of claim 12, wherein the logical evaluation diagnoses a state with a whole replica of the chunk held by at least one storage server and a replication count for erasure-encoded slices that is less than a target number of erasure-encoded slices, and wherein the executable code performs further steps including: assigning an action to the at least one storage server holding a whole replica of the chunk to generate an erasure-encoded slice and replicate the erasure-encoded slice to a storage server in the negotiating group that is selected to hold the slices.
 18. The system of claim 12, wherein the executable code performs further steps including: determining a subset of actions to be performed by the storage server based on the set of roll-call inventory responses; and performing the subset of actions.
 19. The system of claim 18, wherein one storage server in the negotiating group is selected to multicast a new roll-call request for the chunk.
 20. The system of claim 19, wherein the selection of the one storage server in the negotiating group to multicast the new roll-call request comprises: each storage server in the negotiating group pseudo-randomly selecting a time to multicast a new roll-call request for the chunk, wherein the new roll-call request is not issued if pre-empted by receipt of the new roll-call request as multicast by another storage server.
 21. A storage server in a distributed object storage system that stores objects in chunks, the storage server comprising: a processor for executing executable code; memory for storing and accessing executable code and data; and a network connection to communicatively interconnect the storage server with other storage servers in the distributed object storage system, wherein the executable code performs steps including: multicasting a roll-call request to a group of storage servers that are responsible for storing and providing access to a chunk; collecting roll-call inventory responses received from the storage servers in the group to form a set of roll-call inventory responses; and performing a logical evaluation of the set of roll-call inventory responses.
 22. The storage server of claim 21, wherein the logical evaluation results in a subset of actions to be performed by the storage server.
 23. A storage server in a distributed object storage system that stores objects in chunks, the storage server comprising: a processor for executing executable code; memory for storing and accessing executable code and data; and a network connection to communicatively interconnect the storage server with other storage servers in the distributed object storage system, wherein the storage server is a member of a negotiating group for a chunk, and the executable code performs steps including: receiving a roll-call request for the chunk; multicasting a roll-call inventory response to the negotiating group in response to the roll-call request; collecting roll-call inventory responses received from other storage servers in the negotiating group to form a set of roll-call inventory responses; and performing a logical evaluation of the set of roll-call inventory responses.
 24. A method of distributed parity protection of a chunk stored in an object storage cluster, the method comprising: storing the chunk in a plurality of erasure-encoded slices at different storage servers in the object storage cluster, wherein the plurality of erasure-encoded slices include a plurality of data stripes and at least one parity stripe; determining that a data stripe of the plurality of data stripes is lost; determining surviving erasure-encoded slices of the plurality of erasure-encoded slices; grouping the surviving erasure-encoded slices into a first set of pairs, wherein a first storage server holding a first slice of each pair sends the first slice to a second storage server holding a second slice of the pair; and operating on first and second slices of each pair in the first set of pairs to generate a set of resultant slices, wherein the second storage server applies an operation on the first and second slices to generate a resultant slice.
 25. The method of claim 24, further comprising: further grouping slices in the set of resultant slices into a new set of pairs, wherein one storage server holding a first resultant slice of each pair sends the first resultant slice to a different storage server holding a second resultant slice of the pair; and further operating on the first and second resultant slices of each pair in the new set of pairs to generate a new set of resultant slices, wherein said different storage server applies the operation on the first and second resultant slices to generate a new resultant slice.
 26. The method of claim 25, further comprising: repeating the further grouping and further operating steps a plurality of times until a single slice is generated, wherein the single slice is the data stripe that was lost.
 27. The method of claim 24, wherein the operation is an exclusive-or operation.
 28. A distributed object storage system with distributed parity protection, the system comprising: a network; and a plurality of storage servers communicatively interconnected by the network, wherein the plurality of storage servers include executable code that performs steps including: storing a chunk in a plurality of erasure-encoded slices at different storage servers, wherein the plurality of erasure-encoded slices include a plurality of data stripes and at least one parity stripe; determining that a data stripe of the plurality of data stripes is lost; determining surviving erasure-encoded slices of the plurality of erasure-encoded slices; grouping the surviving erasure-encoded slices into a first set of pairs by sending a first erasure-encoded slice of each pair from a first storage server to a second storage server that holds a second erasure-encoded slice of each pair; and operating on first and second slices of each pair in the first set of pairs to generate a set of resultant slices at the second storage server.
 29. The system of claim 28, wherein the executable code performs further steps including: further grouping slices in the set of resultant slices into a new set of pairs by sending a first erasure-encoded slice of each pair in the new set of pairs from one storage server to a different storage server that holds a second erasure-encoded slice of the pair; and further operating on first and second slices of each pair in the new set of pairs to generate a new set of resultant slices at said different storage server.
 30. The system of claim 29, wherein the executable code performs further steps including: repeating the further grouping and further operating steps a plurality of times until a single slice is generated, wherein the single slice is the data stripe that was lost.
 31. The system of claim 28, wherein the operation is an exclusive-or operation. 